From 77a726b30fa249aad4f5c7b4e29e4bec0c23230e Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 11:53:33 +0100
Subject: [PATCH 01/31] fix incorrect emoticon missing space
---
topics/single-cell/index.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/topics/single-cell/index.md b/topics/single-cell/index.md
index 7864ea242a988c..3d5c3d637e8e2a 100644
--- a/topics/single-cell/index.md
+++ b/topics/single-cell/index.md
@@ -13,6 +13,6 @@ Check out workflows shared by users like you!
If you want to help us behind the scenes, from testing workflows and tutorials to building tools, join our Galaxy Single Cell Community of Practice!
- - [Community of Practice](https://galaxyproject.org/projects/singlecell/)
- - [Matrix Chat Forum](https://matrix.to/#/#usegalaxy-eu_single-cell-workflows:gitter.im)
+ - [Community of Practice](https://galaxyproject.org/projects/singlecell/)
+ - [Matrix Chat Forum](https://matrix.to/#/#usegalaxy-eu_single-cell-workflows:gitter.im)
- [Mailing List](https://lists.galaxyproject.org/lists/single-cell-cop.lists.galaxyproject.org/)
From 7c6af3b41d38e2e121f00bc9a5d2d46452eb0fd1 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 11:54:51 +0100
Subject: [PATCH 02/31] remove mention of tutorial mode and subdomain
---
.../scrna-case_FilterPlotandExploreRStudio/preamble.md | 9 ---------
1 file changed, 9 deletions(-)
diff --git a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
index e9b259fd4bdd26..33d405f95699fc 100644
--- a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
+++ b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
@@ -55,15 +55,6 @@ This also alleviates the necessity to convert the AnnData object into a Seurat o
>
{: .hands_on}
-# Important tips for easier analysis
-
-{% snippet faqs/galaxy/tutorial_mode.md %}
-
->
-> - The Galaxy tool search panel sometimes doesn't find the tools we need from the thousands available.
-> - You'll have a much easier time selecting tools from the panel (if you aren't using tutorial mode!) if you are on the [https://humancellatlas.usegalaxy.eu](https://humancellatlas.usegalaxy.eu)
-{: .comment}
-
# Open RStudio in Galaxy
You now should have imported the matrix.mtx, genes.tsv, barcodes.tsv, and exp_design.tsv files into your Galaxy history. For the rest of the workflow, let's move onto RStudio and get coding!
> Open RStudio in Galaxy
From 9eadeca598107b229c5ad97c329e1fd9ae8d65ee Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:02:19 +0100
Subject: [PATCH 03/31] remove duplicate tutorial modes
---
.../preamble.md | 2 +-
.../scrna-case_JUPYTER-trajectories/preamble.md | 11 +----------
.../scrna-case_alevin-combine-datasets/tutorial.md | 2 --
.../tutorials/scrna-case_basic-pipeline/tutorial.md | 2 --
4 files changed, 2 insertions(+), 15 deletions(-)
diff --git a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
index 33d405f95699fc..b9d9c8abae0a0e 100644
--- a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
+++ b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
@@ -56,7 +56,7 @@ This also alleviates the necessity to convert the AnnData object into a Seurat o
{: .hands_on}
# Open RStudio in Galaxy
-You now should have imported the matrix.mtx, genes.tsv, barcodes.tsv, and exp_design.tsv files into your Galaxy history. For the rest of the workflow, let's move onto RStudio and get coding!
+You now should have imported the `matrix.mtx`, `genes.tsv`, `barcodes.tsv`, and `exp_design.tsv` files into your Galaxy history. For the rest of the workflow, let's move onto RStudio and get coding!
> Open RStudio in Galaxy
> Run {% tool [RStudio](interactive_tool_rstudio)%}
{: .hands_on}
diff --git a/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/preamble.md b/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/preamble.md
index 8e60bdadd86bb8..d08fd95981ae5b 100644
--- a/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/preamble.md
+++ b/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/preamble.md
@@ -52,15 +52,6 @@ We've provided you with experimental data to analyse from a mouse dataset of fet
>
{: .hands_on}
-# Important tips for easier analysis
-
-{% snippet faqs/galaxy/tutorial_mode.md %}
-
->
-> - The Galaxy tool search panel sometimes doesn't find the tools we need from the thousands available.
-> - You'll have a much easier time selecting tools from the panel (if you aren't using tutorial mode!) if you are on the [https://humancellatlas.usegalaxy.eu](https://humancellatlas.usegalaxy.eu)
-{: .comment}
-
## Filtering for T-cells
One problem with our current dataset is that it's not just T-cells: we found in the previous tutorial that it also contains macrophages. This is a problem, because trajectory analysis will generally try to find relationships between all the cells in the sample. We need to remove those cell types to analyse the trajectory.
@@ -120,7 +111,7 @@ You have two options for how to proceed with this tutorial - either you download
>
> 1. Open a Terminal in JupyterLab with File -> New -> Terminal
>
-> 2. Run
+> 2. Run
> ```
> wget {{ ipynbpath }}
> ```
diff --git a/topics/single-cell/tutorials/scrna-case_alevin-combine-datasets/tutorial.md b/topics/single-cell/tutorials/scrna-case_alevin-combine-datasets/tutorial.md
index 93a4487a66d1d2..8a06fad5821ebb 100644
--- a/topics/single-cell/tutorials/scrna-case_alevin-combine-datasets/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_alevin-combine-datasets/tutorial.md
@@ -127,8 +127,6 @@ Inspect the {% icon galaxy-eye %} `Experimental Design` text file. This shows yo
## Concatenating objects
-{% snippet faqs/galaxy/tutorial_mode.md %}
-
> Concatenating AnnData objects
>
> 1. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
index 15e3d93b0a9d71..3ecd8fdf93c4b0 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
@@ -118,8 +118,6 @@ You can access the data for this tutorial in multiple ways:
You have generated an annotated AnnData object from your raw scRNA-seq fastq files. However, you have only completed a 'rough' filter of your dataset - there will still be a number of 'cells' that are actually just background from empty droplets or simply low-quality. There will also be genes that could be sequencing artifacts or that appear with such low frequency that statistical tools will fail to analyse them. This background garbage of both cells and genes not only makes it harder to distinguish real biological information from the noise, but also makes it computationally heavy to analyse. These spurious reads take a lot of computational power to analyse! First on our agenda is to filter this matrix to give us cleaner data to extract meaningful insight from, and to allow faster analysis.
-{% snippet faqs/galaxy/tutorial_mode.md %}
-
>
>
> 1. What information is stored in your AnnData object? The last tool to generate this object counted the mitochondrial associated genes in your matrix. Where is that data stored?
From 0ee498f96d7cb7eaef5f025da58be8e8d76d3537 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:14:00 +0100
Subject: [PATCH 04/31] make notebook warning snippet
---
topics/single-cell/faqs/dimension_reduction.md | 2 +-
topics/single-cell/faqs/gene_profile.md | 2 +-
topics/single-cell/faqs/notebook_warning.md | 11 +++++++++++
topics/single-cell/faqs/techniques.md | 2 +-
topics/single-cell/faqs/umi.md | 2 +-
topics/single-cell/faqs/variable_genes.md | 2 +-
.../scrna-case-jupyter_basic-pipeline/tutorial.md | 3 +++
7 files changed, 19 insertions(+), 5 deletions(-)
create mode 100644 topics/single-cell/faqs/notebook_warning.md
diff --git a/topics/single-cell/faqs/dimension_reduction.md b/topics/single-cell/faqs/dimension_reduction.md
index b4cc520c2b1db4..fbc78327ce4af0 100644
--- a/topics/single-cell/faqs/dimension_reduction.md
+++ b/topics/single-cell/faqs/dimension_reduction.md
@@ -3,7 +3,7 @@ redirect_from:
- /topics/transcriptomics/faqs/dimension_reduction
title: Why do we do dimension reduction and then clustering? Why not just cluster on the actual data?
-area: gene
+area: Analysis
box_type: tip
layout: faq
contributors: [rahmot]
diff --git a/topics/single-cell/faqs/gene_profile.md b/topics/single-cell/faqs/gene_profile.md
index eeb1792283effa..06c2ea2e077ca3 100644
--- a/topics/single-cell/faqs/gene_profile.md
+++ b/topics/single-cell/faqs/gene_profile.md
@@ -3,7 +3,7 @@ redirect_from:
- /topics/transcriptomics/faqs/gene_profile
title: What exactly is a ‘Gene profile’?
-area: gene
+area: Interpretation
box_type: tip
layout: faq
contributors: [rahmot]
diff --git a/topics/single-cell/faqs/notebook_warning.md b/topics/single-cell/faqs/notebook_warning.md
new file mode 100644
index 00000000000000..deea6384550c1f
--- /dev/null
+++ b/topics/single-cell/faqs/notebook_warning.md
@@ -0,0 +1,11 @@
+---
+title: Notebook-based tutorials can give different outputs
+area: Analysis
+box_type: warning
+layout: faq
+contributors: [hexhowells, nomadscientist]
+---
+
+The nature of coding pulls the most recent tools to perform tasks. This can - and often does - change the outputs of an analysis. Be prepared, as you are unlikely to get outputs identical to a tutorial if you are running it in a programming environment like a Jupyter Notebook or R-Studio. That's ok! The outputs should still be pretty close.
+
+In the single-cell case study dataset, the basic interpretation has survived 5 years of analytical updates and counting...
diff --git a/topics/single-cell/faqs/techniques.md b/topics/single-cell/faqs/techniques.md
index d9a1638cefac20..299a4c7f8c7977 100644
--- a/topics/single-cell/faqs/techniques.md
+++ b/topics/single-cell/faqs/techniques.md
@@ -3,7 +3,7 @@ redirect_from:
- /topics/transcriptomics/faqs/techniques
title: Can RNA-seq techniques be applied to scRNA-seq?
-area: Single-Cell RNA
+area: Analysis
box_type: tip
layout: faq
contributors: [nomadscientist,mtekman,rahmot]
diff --git a/topics/single-cell/faqs/umi.md b/topics/single-cell/faqs/umi.md
index f17140e0f0a3e7..6cefe033e314f6 100644
--- a/topics/single-cell/faqs/umi.md
+++ b/topics/single-cell/faqs/umi.md
@@ -3,7 +3,7 @@ redirect_from:
- /topics/transcriptomics/faqs/umi
title: Are UMIs not actually unique?
-area: Single-Cell RNA
+area: Analysis
box_type: tip
layout: faq
contributors: [nomadscientist,mtekman]
diff --git a/topics/single-cell/faqs/variable_genes.md b/topics/single-cell/faqs/variable_genes.md
index 2276c8f1f075ce..634aa61587223f 100644
--- a/topics/single-cell/faqs/variable_genes.md
+++ b/topics/single-cell/faqs/variable_genes.md
@@ -3,7 +3,7 @@ redirect_from:
- /topics/transcriptomics/faqs/variable_genes
title: Why do we only consider highly variable genes?
-area: gene
+area: Analysis
box_type: tip
layout: faq
contributors: [rahmot]
diff --git a/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
index 5ffda81b642575..30c046b2cdca0e 100644
--- a/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
@@ -50,6 +50,9 @@ notebook:
snippet: topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/preamble.md
---
+
+{% snippet topics/single-cell/faqs/notebook_warning.md %}
+
> Remember: Notebook-based tutorials can give different outputs!
> The nature of coding pulls the most recent tools to perform tasks. This can - and often does - change the outputs of an analysis. Be prepared, as you are unlikely to get outputs identical to this tutorial. That's ok! The outputs should still be pretty close (the basic interpretation has survived 5 years of analytical updates and counting...).
{: .warning}
From dff467fc59ef43484999e69549042895870ae543 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:20:57 +0100
Subject: [PATCH 05/31] update text
---
topics/single-cell/faqs/notebook_warning.md | 2 --
1 file changed, 2 deletions(-)
diff --git a/topics/single-cell/faqs/notebook_warning.md b/topics/single-cell/faqs/notebook_warning.md
index deea6384550c1f..1aac5fb03f0213 100644
--- a/topics/single-cell/faqs/notebook_warning.md
+++ b/topics/single-cell/faqs/notebook_warning.md
@@ -7,5 +7,3 @@ contributors: [hexhowells, nomadscientist]
---
The nature of coding pulls the most recent tools to perform tasks. This can - and often does - change the outputs of an analysis. Be prepared, as you are unlikely to get outputs identical to a tutorial if you are running it in a programming environment like a Jupyter Notebook or R-Studio. That's ok! The outputs should still be pretty close.
-
-In the single-cell case study dataset, the basic interpretation has survived 5 years of analytical updates and counting...
From 6a99a24b2d48f773424a3ca00fb2df1ace8aa2aa Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:34:53 +0100
Subject: [PATCH 06/31] update fpe tutorial per
https://github.com/galaxyproject/training-material/issues/2799
---
.../scrna-case_basic-pipeline/tutorial.md | 36 ++++++++-----------
1 file changed, 14 insertions(+), 22 deletions(-)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
index 3ecd8fdf93c4b0..5af33da235e0c6 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
@@ -808,34 +808,26 @@ The authors weren't interested in further annotation of the DP cells, so neither
> Annotating clusters
>
-> 1. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
+> 1. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
+> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
+> - *"Change field names in AnnData observations"*
+> - {% icon galaxy-wf-new %} *"Insert Change field names in AnnData observations"*
+> - *"1: Change field names in AnnData observations"*
+> - *"Original name"*: `louvain`
+> - *"New name"*: `cell_type`
+> - *"Keep original"*: {% icon history-share %} `Yes`
+> - This makes a copy of the louvain column, which you can change without altering the original
+>
+> 2. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
> - {% icon param-file %} *"Annotated data matrix"*: `Final object`
> - *"Function to manipulate the object"*: `Rename categories of annotation`
> - *"Key for observations or variables annotation"*: `louvain`
> - *"Comma-separated list of new categories"*: `DP-M4,DP-M3,DP-M1,T-mat,DN,DP-L,DP-M2,Macrophages`
-> - Hang on here, though. This unfortunately deletes the original cluster numbering. Just in case you might want this back, we can add that annotation back in.
->
-> 2. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} with the following parameters:
-> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
-> - *"Copy observations (such as clusters)"*: {% icon history-share %} *Yes*
-> - **Keys from obs to copy**
-> - *"+ Insert Keys from obs to copy"*
-> - *"Key contains"*: `louvain`
-> - {% icon param-file %} *"AnnData objects with obs to copy"*: (output of **Manipulate AnnData** {% icon tool %})
->
-> - You've added the new cell annotations in, now titled `louvain_0`. What, that's not good enough? You want to change the title as well? So be it.
->
-> 3. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
-> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: (output of **AnnData Operations** {% icon tool %})
-> - **Change field names in AnnData observations**
-> - {% icon galaxy-wf-new %} *"+ Insert Change field names in AnnData observations"*
-> - **1: Change field names in AnnData observations**
-> - *"Original name"*: `louvain_0`
-> - *"New name"*: `cell_type`
+> - Note that if you have a slightly different clustering, your list of categories might not match. You could have a different number of categories, or they could be in a different order.
>
-> 4. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
+> 3. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
> - Time to re-plot! {% icon time %} Feel free to re-run {% icon galaxy-refresh %} the **Scanpy PlotEmbed** tool {% icon tool %} on the new object plotting `cell_type` to speed this up. Otherwise...
-> 5. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
+> 4. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"Input object in AnnData/Loom format"*: `Final cell annotated object`
> - *"name of the embedding to plot"*: `umap`
> - *"color by attributes, comma separated texts"*: `sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type`
From 3789eb65c8925920600f461a5bac9d301ff153fd Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:45:26 +0100
Subject: [PATCH 07/31] update workflow with fix
---
...ot_and_Explore_Single-cell_RNA-seq_Data.ga | 2197 +++++++++++++++++
...t_and_Explore_Single-cell_RNA-seq_Data.ga} | 2 +-
2 files changed, 2198 insertions(+), 1 deletion(-)
create mode 100644 Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga => Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga} (99%)
diff --git a/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga b/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
new file mode 100644
index 00000000000000..99c6c10246ea7f
--- /dev/null
+++ b/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
@@ -0,0 +1,2197 @@
+{
+ "a_galaxy_workflow": "true",
+ "annotation": "",
+ "creator": [
+ {
+ "class": "Person",
+ "identifier": "0000-0002-8170-8806",
+ "name": "Wendi Bacon"
+ },
+ {
+ "class": "Person",
+ "identifier": "0009-0001-2017-8805",
+ "name": "Julia Jakiela"
+ }
+ ],
+ "format-version": "0.1",
+ "license": "CC-BY-4.0",
+ "name": "Filter, Plot and Explore Single-cell RNA-seq Data",
+ "steps": {
+ "0": {
+ "annotation": "",
+ "content_id": null,
+ "errors": null,
+ "id": 0,
+ "input_connections": {},
+ "inputs": [
+ {
+ "description": "",
+ "name": "Mito-counted AnnData"
+ }
+ ],
+ "label": "Mito-counted AnnData",
+ "name": "Input dataset",
+ "outputs": [],
+ "position": {
+ "left": 0,
+ "top": 715.0156402587891
+ },
+ "tool_id": null,
+ "tool_state": "{\"optional\": false, \"tag\": null}",
+ "tool_version": null,
+ "type": "data_input",
+ "uuid": "12249163-a3de-445f-95cd-a7a627da5076",
+ "when": null,
+ "workflow_outputs": []
+ },
+ "1": {
+ "annotation": "",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
+ "errors": null,
+ "id": 1,
+ "input_connections": {
+ "input": {
+ "id": 0,
+ "output_name": "output"
+ }
+ },
+ "inputs": [],
+ "label": null,
+ "name": "Inspect AnnData",
+ "outputs": [
+ {
+ "name": "obs",
+ "type": "tabular"
+ }
+ ],
+ "position": {
+ "left": 277.87506103515625,
+ "top": 0
+ },
+ "post_job_actions": {},
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
+ "tool_shed_repository": {
+ "changeset_revision": "ee98d611afc6",
+ "name": "anndata_inspect",
+ "owner": "iuc",
+ "tool_shed": "toolshed.g2.bx.psu.edu"
+ },
+ "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
+ "type": "tool",
+ "uuid": "71e5aa83-23a9-467b-bcf8-50dfe4a98331",
+ "when": null,
+ "workflow_outputs": [
+ {
+ "label": null,
+ "output_name": "obs",
+ "uuid": "a47dc402-352e-4878-9b0e-da86ca690f92"
+ }
+ ]
+ },
+ "2": {
+ "annotation": "",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9",
+ "errors": null,
+ "id": 2,
+ "input_connections": {
+ "input_obj_file": {
+ "id": 0,
+ "output_name": "output"
+ }
+ },
+ "inputs": [],
+ "label": null,
+ "name": "Scanpy FilterCells",
+ "outputs": [
+ {
+ "name": "output_h5ad",
+ "type": "h5ad"
+ }
+ ],
+ "position": {
+ "left": 277.87506103515625,
+ "top": 217.06249237060547
+ },
+ "post_job_actions": {
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\ No newline at end of file
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
similarity index 99%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
index b806556141af9f..db6749dd548097 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
@@ -2179,4 +2179,4 @@
],
"uuid": "3d42c837-d379-4f2f-bc4d-08d7b502afe6",
"version": 7
-}
\ No newline at end of file
+}
From d4d56d7f48aa4188e81525b63c817e980722a3cc Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:54:06 +0100
Subject: [PATCH 08/31] add notebook warnings
---
.../tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md | 4 ----
.../scrna-case_FilterPlotandExploreRStudio/tutorial.md | 2 ++
.../tutorials/scrna-case_JUPYTER-trajectories/tutorial.md | 2 ++
.../tutorials/scrna-case_monocle3-rstudio/tutorial.md | 2 ++
4 files changed, 6 insertions(+), 4 deletions(-)
diff --git a/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
index 30c046b2cdca0e..6474e028120a93 100644
--- a/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
@@ -53,10 +53,6 @@ notebook:
{% snippet topics/single-cell/faqs/notebook_warning.md %}
-> Remember: Notebook-based tutorials can give different outputs!
-> The nature of coding pulls the most recent tools to perform tasks. This can - and often does - change the outputs of an analysis. Be prepared, as you are unlikely to get outputs identical to this tutorial. That's ok! The outputs should still be pretty close (the basic interpretation has survived 5 years of analytical updates and counting...).
-{: .warning}
-
# Install libraries
This tutorial requies some libraries to be installed which is done below (igraph and louvain are not used directly and are just required for plotting). The ```-q``` parameter hides most of the outputs of the installation in order to make the notebook a bit cleaner. If there are any issues with the installation, then removing this parameter may give you more information about the issue.
diff --git a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md
index 7e86cee0167a64..a68a251fc28a99 100644
--- a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md
@@ -55,6 +55,8 @@ notebook:
snippet: topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
---
+{% snippet topics/single-cell/faqs/notebook_warning.md %}
+
# Setting your environment
First thing's first, we need to load the packages we will be using. In order to use any functions of a package, we must first call the library of that package. In your console (likely in the lower left corner of your RStudio window), run the following lines of code to do so:
diff --git a/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md b/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md
index e13b7877bfeda9..4285cee64e1371 100644
--- a/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md
@@ -52,6 +52,8 @@ notebook:
From now on, you can view this tutorial in the Jupyter notebook, which will allow you to read the material and simultaneously execute the code cells! You may have to change certain numbers in the code blocks, so do read carefully. The tutorial is adapted from the [Scanpy Trajectory inference tutorial](https://scanpy-tutorials.readthedocs.io/en/latest/paga-paul15.html).
+{% snippet topics/single-cell/faqs/notebook_warning.md %}
+
## Install modules & activate them
```python
diff --git a/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md b/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md
index 35d2a4f5b6a8e5..49f2678ec7193f 100644
--- a/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md
@@ -56,6 +56,8 @@ notebook:
snippet: topics/single-cell/tutorials/scrna-case_monocle3-rstudio/preamble.md
---
+{% snippet topics/single-cell/faqs/notebook_warning.md %}
+
## Setting up the environment and file upload
Once the installation is done, we should load the needed packages into our notebook. Navigate back to your `notebook`. If you are using our prepopulated notebook, you can follow the tutorial from there. Otherwise, input the following into your fresh notebook.
From 5190e86cee503dbeca360f2282796a63f0043d4a Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 13:47:18 +0100
Subject: [PATCH 09/31] Delete
Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
---
...ot_and_Explore_Single-cell_RNA-seq_Data.ga | 2197 -----------------
1 file changed, 2197 deletions(-)
delete mode 100644 Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
diff --git a/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga b/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
deleted file mode 100644
index 99c6c10246ea7f..00000000000000
--- a/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
+++ /dev/null
@@ -1,2197 +0,0 @@
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From 6dd83f60e160771656334bd13f9c3b5d1f083142 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 13:48:31 +0100
Subject: [PATCH 10/31] iconify images
---
_config.yml | 1 +
topics/single-cell/index.md | 6 +++---
2 files changed, 4 insertions(+), 3 deletions(-)
diff --git a/_config.yml b/_config.yml
index 9c0ec0e3c54870..d405034ed8ed01 100644
--- a/_config.yml
+++ b/_config.yml
@@ -164,6 +164,7 @@ icon-tag:
param-select: fas fa-filter
param-text: fas fa-pencil-alt
param-toggle: fas fa-toggle-on
+ point-right: fa fa-hand-o-right
pref-info: fas fa-user
pref-password: fas fa-unlock-alt
pref-identities: far fa-id-card-o
diff --git a/topics/single-cell/index.md b/topics/single-cell/index.md
index 3d5c3d637e8e2a..e402d143abf77f 100644
--- a/topics/single-cell/index.md
+++ b/topics/single-cell/index.md
@@ -13,6 +13,6 @@ Check out workflows shared by users like you!
If you want to help us behind the scenes, from testing workflows and tutorials to building tools, join our Galaxy Single Cell Community of Practice!
- - [Community of Practice](https://galaxyproject.org/projects/singlecell/)
- - [Matrix Chat Forum](https://matrix.to/#/#usegalaxy-eu_single-cell-workflows:gitter.im)
- - [Mailing List](https://lists.galaxyproject.org/lists/single-cell-cop.lists.galaxyproject.org/)
+ - {% icon point-right %} [Community of Practice](https://galaxyproject.org/projects/singlecell/)
+ - {% icon feedback %} [Matrix Chat Forum](https://matrix.to/#/#usegalaxy-eu_single-cell-workflows:gitter.im)
+ - {% icon email %} [Mailing List](https://lists.galaxyproject.org/lists/single-cell-cop.lists.galaxyproject.org/)
From 6d8a1656142edcdbaa30abeec0b93b7251022f84 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 14:11:53 +0100
Subject: [PATCH 11/31] rename test
I just rearranged two naming tools, so this shouldn't be different...
---
...,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
index 9a5fefcafa1e26..03b284b4b4d86f 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
@@ -1,4 +1,4 @@
-- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated
+- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data
job:
Mito-counted AnnData:
class: File
From 45d1e52d03374f9c35c51d5e57887d4804bc243d Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 14:13:38 +0100
Subject: [PATCH 12/31] updated workflow license
---
...ot_and_Explore_Single-cell_RNA-seq_Data.ga | 863 +++++++++---------
1 file changed, 439 insertions(+), 424 deletions(-)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
index db6749dd548097..99c6c10246ea7f 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
@@ -1,8 +1,21 @@
{
"a_galaxy_workflow": "true",
- "annotation": "Updated tool versions Aug 24 2022",
+ "annotation": "",
+ "creator": [
+ {
+ "class": "Person",
+ "identifier": "0000-0002-8170-8806",
+ "name": "Wendi Bacon"
+ },
+ {
+ "class": "Person",
+ "identifier": "0009-0001-2017-8805",
+ "name": "Julia Jakiela"
+ }
+ ],
"format-version": "0.1",
- "name": "CS3_Filter, Plot and Explore Single-cell RNA-seq Data",
+ "license": "CC-BY-4.0",
+ "name": "Filter, Plot and Explore Single-cell RNA-seq Data",
"steps": {
"0": {
"annotation": "",
@@ -21,13 +34,14 @@
"outputs": [],
"position": {
"left": 0,
- "top": 736.1875
+ "top": 715.0156402587891
},
"tool_id": null,
"tool_state": "{\"optional\": false, \"tag\": null}",
"tool_version": null,
"type": "data_input",
- "uuid": "60316d4a-07b0-4eea-a889-eef54798c5e0",
+ "uuid": "12249163-a3de-445f-95cd-a7a627da5076",
+ "when": null,
"workflow_outputs": []
},
"1": {
@@ -51,8 +65,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 21.0703125
+ "left": 277.87506103515625,
+ "top": 0
},
"post_job_actions": {},
"tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
@@ -62,21 +76,22 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"__input_ext\": \"h5ad\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "0.7.5+galaxy1",
+ "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "99ffbf79-3be8-4905-b978-e56b02327314",
+ "uuid": "71e5aa83-23a9-467b-bcf8-50dfe4a98331",
+ "when": null,
"workflow_outputs": [
{
"label": null,
"output_name": "obs",
- "uuid": "6e2bd8b0-8203-4dfe-9c28-054d863bd277"
+ "uuid": "a47dc402-352e-4878-9b0e-da86ca690f92"
}
]
},
"2": {
"annotation": "",
- "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy0",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9",
"errors": null,
"id": 2,
"input_connections": {
@@ -95,8 +110,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 238.2421875
+ "left": 277.87506103515625,
+ "top": 217.06249237060547
},
"post_job_actions": {
"RenameDatasetActionoutput_h5ad": {
@@ -107,22 +122,23 @@
"output_name": "output_h5ad"
}
},
- "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy0",
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9",
"tool_shed_repository": {
- "changeset_revision": "55ccc0a121bc",
+ "changeset_revision": "e9283529cba1",
"name": "scanpy_filter_cells",
"owner": "ebi-gxa",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"categories\": [], \"export_mtx\": \"false\", \"force_recalc\": \"false\", \"gene_name\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"output_format\": \"anndata_h5ad\", \"parameters\": [{\"__index__\": 0, \"name\": \"log1p_n_genes_by_counts\", \"min\": \"5.7\", \"max\": \"20.0\"}], \"save_layer\": null, \"save_raw\": \"false\", \"subsets\": [], \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.8.1+galaxy0",
+ "tool_state": "{\"categories\": [], \"export_mtx\": false, \"force_recalc\": false, \"gene_name\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"output_format\": \"anndata_h5ad\", \"parameters\": [{\"__index__\": 0, \"name\": \"log1p_n_genes_by_counts\", \"min\": \"5.7\", \"max\": \"20.0\"}], \"save_layer\": null, \"save_raw\": false, \"subsets\": [], \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "ab02dab9-1c72-4987-929c-6b67baae1e6d",
+ "uuid": "2b0750ea-ffb2-436a-91b3-2f0f796f18d7",
+ "when": null,
"workflow_outputs": [
{
"label": "Genes-filtered Object",
"output_name": "output_h5ad",
- "uuid": "08175d7f-f4f4-413c-ad86-f59587ff692e"
+ "uuid": "c132bfef-6484-45ab-b634-8e25e408deea"
}
]
},
@@ -147,8 +163,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 434.28125
+ "left": 277.87506103515625,
+ "top": 413.0937194824219
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -166,15 +182,16 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_total_counts\", \"y\": \"log1p_n_genes_by_counts\", \"color\": \"pct_counts_mito\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": \"false\", \"sort_order\": \"true\", \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": \"true\", \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.7.1+galaxy1",
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_total_counts\", \"y\": \"log1p_n_genes_by_counts\", \"color\": \"pct_counts_mito\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": false, \"sort_order\": true, \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": true, \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "767da31e-dc80-4d11-9f8e-8b1589029dcc",
+ "uuid": "95975f35-24be-4e65-8830-ad18b5fa7943",
+ "when": null,
"workflow_outputs": [
{
"label": "Scatter - genes x UMIs",
"output_name": "out_png",
- "uuid": "bfc499ee-630a-498b-9be6-696d9bb78837"
+ "uuid": "58e53e50-4bf8-4980-8f74-40198c29bbb7"
}
]
},
@@ -199,8 +216,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 588.25
+ "left": 277.87506103515625,
+ "top": 567.0468902587891
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -218,15 +235,16 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_n_genes_by_counts\", \"y\": \"pct_counts_mito\", \"color\": \"\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": \"false\", \"sort_order\": \"true\", \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": \"true\", \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.7.1+galaxy1",
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_n_genes_by_counts\", \"y\": \"pct_counts_mito\", \"color\": \"\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": false, \"sort_order\": true, \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": true, \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "ad0b1195-4bb2-46be-bb8a-8fd5de416372",
+ "uuid": "984cec24-7821-4fe6-868c-eaca648439b0",
+ "when": null,
"workflow_outputs": [
{
"label": "Scatter - mito x genes",
"output_name": "out_png",
- "uuid": "f2c78ef3-7d31-4930-954c-0133cce27a41"
+ "uuid": "5976a26f-7e4a-4af4-bda4-0dd0dc7c8ef8"
}
]
},
@@ -251,8 +269,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 742.28125
+ "left": 278.98952554536163,
+ "top": 721.0843561275927
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -270,15 +288,16 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"genotype\", \"log\": \"false\", \"use_raw\": \"false\", \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.7.1+galaxy1",
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"genotype\", \"log\": false, \"use_raw\": false, \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "a6a5b2f9-9765-4f5d-b4cf-7c513b8eed3c",
+ "uuid": "0fe5d1b1-9eff-4043-98b1-7ecdd85dafac",
+ "when": null,
"workflow_outputs": [
{
"label": "Violin - genotype - log",
"output_name": "out_png",
- "uuid": "348818e6-9def-41fd-a390-6f8525c57cd8"
+ "uuid": "06c5979a-2e2e-4030-9c5b-adfafd85f7a7"
}
]
},
@@ -303,8 +322,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 896.3046875
+ "left": 277.87506103515625,
+ "top": 875.0937652587891
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -322,15 +341,16 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"batch\", \"log\": \"false\", \"use_raw\": \"false\", \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.7.1+galaxy1",
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"batch\", \"log\": false, \"use_raw\": false, \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "a6d8ecf9-1510-4c1a-8665-ddf25b0ca395",
+ "uuid": "8ee0819d-d8a7-4a08-a3bf-9431a86ae9fa",
+ "when": null,
"workflow_outputs": [
{
"label": "Violin - batch - log",
"output_name": "out_png",
- "uuid": "844f5e7c-78c8-4f28-8e15-cea35ada8fef"
+ "uuid": "e78d661e-c014-4fad-91ef-af4cd99877c5"
}
]
},
@@ -355,8 +375,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 1029.3046875
+ "left": 277.8749630368968,
+ "top": 1008.0844487787456
},
"post_job_actions": {},
"tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
@@ -366,15 +386,16 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"__input_ext\": \"h5ad\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"var\", \"__current_case__\": 4}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "0.7.5+galaxy1",
+ "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"var\", \"__current_case__\": 4}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "9445c5ea-8c75-48f2-b7a1-fd0e43c625c7",
+ "uuid": "1a0e6ed5-2a34-46bb-a028-8a7e7859ed1d",
+ "when": null,
"workflow_outputs": [
{
"label": null,
"output_name": "var",
- "uuid": "ba910718-a539-4b77-b3e8-087711e13eaf"
+ "uuid": "412e54d9-d405-430b-b75b-e748237b8c1f"
}
]
},
@@ -399,8 +420,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 1267.2734375
+ "left": 279.20030309822187,
+ "top": 1246.0718715988953
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -418,15 +439,16 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
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- "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,log1p_total_counts,Hba-a1,cell_type\", \"components\": \"\", \"edges\": \"false\", \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": \"false\", \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"RuntimeValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": \"false\", \"use_raw\": \"false\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.8.1+galaxy0",
+ "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type\", \"components\": \"\", \"edges\": false, \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": false, \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": false, \"use_raw\": false, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "ff379bdf-e875-4803-baa0-b11bd71666db",
+ "uuid": "6185e50d-2359-47e4-9a65-73215705e21c",
+ "when": null,
"workflow_outputs": [
{
"label": null,
"output_name": "output_png",
- "uuid": "cb97c2f3-8e23-45d0-bc96-faf2f06b59d0"
+ "uuid": "c81c00cf-3087-4dee-8b1e-83e16db3b2af"
}
]
}
},
"tags": [
- "name:transcriptomics",
- "name:training",
- "name:singlecell"
+ "name:singlecell",
+ "name:training"
],
- "uuid": "3d42c837-d379-4f2f-bc4d-08d7b502afe6",
- "version": 7
-}
+ "uuid": "a765a07e-1354-4c38-98a2-fe141e4871ed",
+ "version": 1
+}
\ No newline at end of file
From f65ed0e689d9c0373cabf7f1501c919305558e44 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 14:23:47 +0100
Subject: [PATCH 13/31] rename
---
...=> Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml} | 0
1 file changed, 0 insertions(+), 0 deletions(-)
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml => Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml} (100%)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
similarity index 100%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
From 069eaa35e7a878ce8c779374a9cef758e4cfd233 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:54:06 +0100
Subject: [PATCH 14/31] add notebook warnings
---
.../tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md | 4 ----
.../scrna-case_FilterPlotandExploreRStudio/tutorial.md | 2 ++
.../tutorials/scrna-case_JUPYTER-trajectories/tutorial.md | 2 ++
.../tutorials/scrna-case_monocle3-rstudio/tutorial.md | 2 ++
4 files changed, 6 insertions(+), 4 deletions(-)
diff --git a/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
index 30c046b2cdca0e..6474e028120a93 100644
--- a/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case-jupyter_basic-pipeline/tutorial.md
@@ -53,10 +53,6 @@ notebook:
{% snippet topics/single-cell/faqs/notebook_warning.md %}
-> Remember: Notebook-based tutorials can give different outputs!
-> The nature of coding pulls the most recent tools to perform tasks. This can - and often does - change the outputs of an analysis. Be prepared, as you are unlikely to get outputs identical to this tutorial. That's ok! The outputs should still be pretty close (the basic interpretation has survived 5 years of analytical updates and counting...).
-{: .warning}
-
# Install libraries
This tutorial requies some libraries to be installed which is done below (igraph and louvain are not used directly and are just required for plotting). The ```-q``` parameter hides most of the outputs of the installation in order to make the notebook a bit cleaner. If there are any issues with the installation, then removing this parameter may give you more information about the issue.
diff --git a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md
index 7e86cee0167a64..a68a251fc28a99 100644
--- a/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/tutorial.md
@@ -55,6 +55,8 @@ notebook:
snippet: topics/single-cell/tutorials/scrna-case_FilterPlotandExploreRStudio/preamble.md
---
+{% snippet topics/single-cell/faqs/notebook_warning.md %}
+
# Setting your environment
First thing's first, we need to load the packages we will be using. In order to use any functions of a package, we must first call the library of that package. In your console (likely in the lower left corner of your RStudio window), run the following lines of code to do so:
diff --git a/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md b/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md
index e13b7877bfeda9..4285cee64e1371 100644
--- a/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_JUPYTER-trajectories/tutorial.md
@@ -52,6 +52,8 @@ notebook:
From now on, you can view this tutorial in the Jupyter notebook, which will allow you to read the material and simultaneously execute the code cells! You may have to change certain numbers in the code blocks, so do read carefully. The tutorial is adapted from the [Scanpy Trajectory inference tutorial](https://scanpy-tutorials.readthedocs.io/en/latest/paga-paul15.html).
+{% snippet topics/single-cell/faqs/notebook_warning.md %}
+
## Install modules & activate them
```python
diff --git a/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md b/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md
index 35d2a4f5b6a8e5..49f2678ec7193f 100644
--- a/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_monocle3-rstudio/tutorial.md
@@ -56,6 +56,8 @@ notebook:
snippet: topics/single-cell/tutorials/scrna-case_monocle3-rstudio/preamble.md
---
+{% snippet topics/single-cell/faqs/notebook_warning.md %}
+
## Setting up the environment and file upload
Once the installation is done, we should load the needed packages into our notebook. Navigate back to your `notebook`. If you are using our prepopulated notebook, you can follow the tutorial from there. Otherwise, input the following into your fresh notebook.
From 8d83b38fc94f4ba95e93595b55303025a4840588 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 13:48:31 +0100
Subject: [PATCH 15/31] iconify images
---
_config.yml | 1 +
topics/single-cell/index.md | 6 +++---
2 files changed, 4 insertions(+), 3 deletions(-)
diff --git a/_config.yml b/_config.yml
index 9c0ec0e3c54870..d405034ed8ed01 100644
--- a/_config.yml
+++ b/_config.yml
@@ -164,6 +164,7 @@ icon-tag:
param-select: fas fa-filter
param-text: fas fa-pencil-alt
param-toggle: fas fa-toggle-on
+ point-right: fa fa-hand-o-right
pref-info: fas fa-user
pref-password: fas fa-unlock-alt
pref-identities: far fa-id-card-o
diff --git a/topics/single-cell/index.md b/topics/single-cell/index.md
index 3d5c3d637e8e2a..e402d143abf77f 100644
--- a/topics/single-cell/index.md
+++ b/topics/single-cell/index.md
@@ -13,6 +13,6 @@ Check out workflows shared by users like you!
If you want to help us behind the scenes, from testing workflows and tutorials to building tools, join our Galaxy Single Cell Community of Practice!
- - [Community of Practice](https://galaxyproject.org/projects/singlecell/)
- - [Matrix Chat Forum](https://matrix.to/#/#usegalaxy-eu_single-cell-workflows:gitter.im)
- - [Mailing List](https://lists.galaxyproject.org/lists/single-cell-cop.lists.galaxyproject.org/)
+ - {% icon point-right %} [Community of Practice](https://galaxyproject.org/projects/singlecell/)
+ - {% icon feedback %} [Matrix Chat Forum](https://matrix.to/#/#usegalaxy-eu_single-cell-workflows:gitter.im)
+ - {% icon email %} [Mailing List](https://lists.galaxyproject.org/lists/single-cell-cop.lists.galaxyproject.org/)
From f2d6314909ec8ac00139cc6253b41a0f7634a23e Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 12:34:53 +0100
Subject: [PATCH 16/31] FPE fixes
rename
rename test
I just rearranged two naming tools, so this shouldn't be different...
Delete Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
update workflow with fix
update fpe tutorial per https://github.com/galaxyproject/training-material/issues/2799
---
.../scrna-case_basic-pipeline/tutorial.md | 36 +-
...Explore-Single-cell-RNA-seq-Data-test.yml} | 2 +-
...t_and_Explore_Single-cell_RNA-seq_Data.ga} | 861 +++++++++---------
3 files changed, 453 insertions(+), 446 deletions(-)
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml => Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml} (99%)
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga => Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga} (64%)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
index 3ecd8fdf93c4b0..5af33da235e0c6 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
@@ -808,34 +808,26 @@ The authors weren't interested in further annotation of the DP cells, so neither
> Annotating clusters
>
-> 1. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
+> 1. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
+> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
+> - *"Change field names in AnnData observations"*
+> - {% icon galaxy-wf-new %} *"Insert Change field names in AnnData observations"*
+> - *"1: Change field names in AnnData observations"*
+> - *"Original name"*: `louvain`
+> - *"New name"*: `cell_type`
+> - *"Keep original"*: {% icon history-share %} `Yes`
+> - This makes a copy of the louvain column, which you can change without altering the original
+>
+> 2. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
> - {% icon param-file %} *"Annotated data matrix"*: `Final object`
> - *"Function to manipulate the object"*: `Rename categories of annotation`
> - *"Key for observations or variables annotation"*: `louvain`
> - *"Comma-separated list of new categories"*: `DP-M4,DP-M3,DP-M1,T-mat,DN,DP-L,DP-M2,Macrophages`
-> - Hang on here, though. This unfortunately deletes the original cluster numbering. Just in case you might want this back, we can add that annotation back in.
->
-> 2. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} with the following parameters:
-> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
-> - *"Copy observations (such as clusters)"*: {% icon history-share %} *Yes*
-> - **Keys from obs to copy**
-> - *"+ Insert Keys from obs to copy"*
-> - *"Key contains"*: `louvain`
-> - {% icon param-file %} *"AnnData objects with obs to copy"*: (output of **Manipulate AnnData** {% icon tool %})
->
-> - You've added the new cell annotations in, now titled `louvain_0`. What, that's not good enough? You want to change the title as well? So be it.
->
-> 3. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
-> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: (output of **AnnData Operations** {% icon tool %})
-> - **Change field names in AnnData observations**
-> - {% icon galaxy-wf-new %} *"+ Insert Change field names in AnnData observations"*
-> - **1: Change field names in AnnData observations**
-> - *"Original name"*: `louvain_0`
-> - *"New name"*: `cell_type`
+> - Note that if you have a slightly different clustering, your list of categories might not match. You could have a different number of categories, or they could be in a different order.
>
-> 4. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
+> 3. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
> - Time to re-plot! {% icon time %} Feel free to re-run {% icon galaxy-refresh %} the **Scanpy PlotEmbed** tool {% icon tool %} on the new object plotting `cell_type` to speed this up. Otherwise...
-> 5. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
+> 4. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"Input object in AnnData/Loom format"*: `Final cell annotated object`
> - *"name of the embedding to plot"*: `umap`
> - *"color by attributes, comma separated texts"*: `sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type`
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
similarity index 99%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
index 9a5fefcafa1e26..03b284b4b4d86f 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
@@ -1,4 +1,4 @@
-- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated
+- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data
job:
Mito-counted AnnData:
class: File
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
similarity index 64%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
index b806556141af9f..99c6c10246ea7f 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
@@ -1,8 +1,21 @@
{
"a_galaxy_workflow": "true",
- "annotation": "Updated tool versions Aug 24 2022",
+ "annotation": "",
+ "creator": [
+ {
+ "class": "Person",
+ "identifier": "0000-0002-8170-8806",
+ "name": "Wendi Bacon"
+ },
+ {
+ "class": "Person",
+ "identifier": "0009-0001-2017-8805",
+ "name": "Julia Jakiela"
+ }
+ ],
"format-version": "0.1",
- "name": "CS3_Filter, Plot and Explore Single-cell RNA-seq Data",
+ "license": "CC-BY-4.0",
+ "name": "Filter, Plot and Explore Single-cell RNA-seq Data",
"steps": {
"0": {
"annotation": "",
@@ -21,13 +34,14 @@
"outputs": [],
"position": {
"left": 0,
- "top": 736.1875
+ "top": 715.0156402587891
},
"tool_id": null,
"tool_state": "{\"optional\": false, \"tag\": null}",
"tool_version": null,
"type": "data_input",
- "uuid": "60316d4a-07b0-4eea-a889-eef54798c5e0",
+ "uuid": "12249163-a3de-445f-95cd-a7a627da5076",
+ "when": null,
"workflow_outputs": []
},
"1": {
@@ -51,8 +65,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 21.0703125
+ "left": 277.87506103515625,
+ "top": 0
},
"post_job_actions": {},
"tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
@@ -62,21 +76,22 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"__input_ext\": \"h5ad\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "0.7.5+galaxy1",
+ "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "99ffbf79-3be8-4905-b978-e56b02327314",
+ "uuid": "71e5aa83-23a9-467b-bcf8-50dfe4a98331",
+ "when": null,
"workflow_outputs": [
{
"label": null,
"output_name": "obs",
- "uuid": "6e2bd8b0-8203-4dfe-9c28-054d863bd277"
+ "uuid": "a47dc402-352e-4878-9b0e-da86ca690f92"
}
]
},
"2": {
"annotation": "",
- "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy0",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9",
"errors": null,
"id": 2,
"input_connections": {
@@ -95,8 +110,8 @@
}
],
"position": {
- "left": 277.8984375,
- "top": 238.2421875
+ "left": 277.87506103515625,
+ "top": 217.06249237060547
},
"post_job_actions": {
"RenameDatasetActionoutput_h5ad": {
@@ -107,22 +122,23 @@
"output_name": "output_h5ad"
}
},
- "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy0",
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9",
"tool_shed_repository": {
- "changeset_revision": "55ccc0a121bc",
+ "changeset_revision": "e9283529cba1",
"name": "scanpy_filter_cells",
"owner": "ebi-gxa",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"categories\": [], \"export_mtx\": \"false\", \"force_recalc\": \"false\", \"gene_name\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"output_format\": \"anndata_h5ad\", \"parameters\": [{\"__index__\": 0, \"name\": \"log1p_n_genes_by_counts\", \"min\": \"5.7\", \"max\": \"20.0\"}], \"save_layer\": null, \"save_raw\": \"false\", \"subsets\": [], \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.8.1+galaxy0",
+ "tool_state": "{\"categories\": [], \"export_mtx\": false, \"force_recalc\": false, \"gene_name\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"output_format\": \"anndata_h5ad\", \"parameters\": [{\"__index__\": 0, \"name\": \"log1p_n_genes_by_counts\", \"min\": \"5.7\", \"max\": \"20.0\"}], \"save_layer\": null, \"save_raw\": false, \"subsets\": [], \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "ab02dab9-1c72-4987-929c-6b67baae1e6d",
+ "uuid": "2b0750ea-ffb2-436a-91b3-2f0f796f18d7",
+ "when": null,
"workflow_outputs": [
{
"label": "Genes-filtered Object",
"output_name": "output_h5ad",
- "uuid": "08175d7f-f4f4-413c-ad86-f59587ff692e"
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@@ -147,8 +163,8 @@
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@@ -166,15 +182,16 @@
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"output_name": "out_png",
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@@ -199,8 +216,8 @@
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@@ -218,15 +235,16 @@
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@@ -251,8 +269,8 @@
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@@ -270,15 +288,16 @@
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@@ -303,8 +322,8 @@
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@@ -322,15 +341,16 @@
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@@ -355,8 +375,8 @@
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@@ -366,15 +386,16 @@
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@@ -399,8 +420,8 @@
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@@ -418,15 +439,16 @@
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@@ -451,8 +473,8 @@
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@@ -462,15 +484,16 @@
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- "tool_version": "0.7.5+galaxy1",
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@@ -495,8 +518,8 @@
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@@ -514,15 +537,16 @@
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- "tool_version": "1.7.1+galaxy1",
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- "uuid": "a639cdc0-da40-4df9-8348-23117528b24a"
+ "uuid": "9af5fbd8-904d-4ce1-a2bd-c4538211bc37"
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@@ -547,8 +571,8 @@
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@@ -566,21 +590,22 @@
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- "tool_version": "1.7.1+galaxy1",
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@@ -599,8 +624,8 @@
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"output_name": "var"
}
},
@@ -1919,35 +1942,36 @@
}
],
"position": {
- "left": 4190.2109375,
- "top": 976.3046875
+ "left": 4190.000076293945,
+ "top": 955.0937652587891
},
"post_job_actions": {},
"tool_id": "join1",
"tool_state": "{\"__input_ext\": \"tabular\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"field1\": \"4\", \"field2\": \"2\", \"fill_empty_columns\": {\"fill_empty_columns_switch\": \"no_fill\", \"__current_case__\": 0}, \"header\": \"-H\", \"input1\": {\"__class__\": \"ConnectedValue\"}, \"input2\": {\"__class__\": \"ConnectedValue\"}, \"partial\": \"-p\", \"unmatched\": \"-u\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "2.1.3",
+ "tool_version": null,
"type": "tool",
- "uuid": "db6d5777-a3dd-467d-8541-91bb998e0e72",
+ "uuid": "865701b0-5ef2-4a42-b9d1-ce39423dc775",
+ "when": null,
"workflow_outputs": [
{
"label": null,
"output_name": "out_file1",
- "uuid": "cb6967d5-7390-4d2e-b2c4-1d8a9e2d3c69"
+ "uuid": "ebddb6c4-a4a9-4ca2-b9ac-87796242b88d"
}
]
},
- "39": {
+ "38": {
"annotation": "",
"content_id": "join1",
"errors": null,
- "id": 39,
+ "id": 38,
"input_connections": {
"input1": {
"id": 31,
"output_name": "output_tsv"
},
"input2": {
- "id": 36,
+ "id": 35,
"output_name": "var"
}
},
@@ -1961,83 +1985,77 @@
}
],
"position": {
- "left": 4178.2109375,
- "top": 1199.2890625
+ "left": 4190.000076293945,
+ "top": 1140.0936889648438
},
"post_job_actions": {},
"tool_id": "join1",
- "tool_state": "{\"field1\": \"4\", \"field2\": \"2\", \"fill_empty_columns\": {\"fill_empty_columns_switch\": \"no_fill\", \"__current_case__\": 0}, \"header\": \"-H\", \"input1\": {\"__class__\": \"ConnectedValue\"}, \"input2\": {\"__class__\": \"ConnectedValue\"}, \"partial\": \"-p\", \"unmatched\": \"-u\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "2.1.3",
+ "tool_state": "{\"__input_ext\": \"tabular\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"field1\": \"4\", \"field2\": \"2\", \"fill_empty_columns\": {\"fill_empty_columns_switch\": \"no_fill\", \"__current_case__\": 0}, \"header\": \"-H\", \"input1\": {\"__class__\": \"ConnectedValue\"}, \"input2\": {\"__class__\": \"ConnectedValue\"}, \"partial\": \"-p\", \"unmatched\": \"-u\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "f4db0e7d-dfc8-4f77-bca0-997a0347304b",
+ "uuid": "4381f3df-c621-4c92-8598-de5ee9c46a64",
+ "when": null,
"workflow_outputs": [
{
"label": null,
"output_name": "out_file1",
- "uuid": "54cdb2bd-437b-47e4-90c1-e99e0b468574"
+ "uuid": "87490b1e-f4b9-4ded-8751-c4eff7859b8c"
}
]
},
- "40": {
+ "39": {
"annotation": "",
- "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1",
"errors": null,
- "id": 40,
+ "id": 39,
"input_connections": {
- "input_obj_file": {
- "id": 37,
+ "input": {
+ "id": 36,
"output_name": "output_h5ad"
}
},
"inputs": [],
"label": null,
- "name": "AnnData Operations",
+ "name": "Manipulate AnnData",
"outputs": [
{
- "name": "output_h5ad",
+ "name": "anndata",
"type": "h5ad"
}
],
"position": {
- "left": 4468.2109375,
- "top": 0
+ "left": 4178.84374609375,
+ "top": 195.09375
},
- "post_job_actions": {
- "RenameDatasetActionoutput_h5ad": {
- "action_arguments": {
- "newname": "Final cell annotated object"
- },
- "action_type": "RenameDatasetAction",
- "output_name": "output_h5ad"
- }
- },
- "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0",
+ "post_job_actions": {},
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1",
"tool_shed_repository": {
- "changeset_revision": "890fb06a2893",
- "name": "anndata_ops",
- "owner": "ebi-gxa",
+ "changeset_revision": "3d748954434b",
+ "name": "anndata_manipulate",
+ "owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"copy_adata_to_raw\": \"false\", \"copy_e\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_l\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_o\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_r\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_u\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_x\": {\"default\": \"false\", \"__current_case__\": 1}, \"gene_flags\": [], \"gene_symbols_field\": \"index\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"modifications\": [{\"__index__\": 0, \"from_obs\": \"louvain_0\", \"to_obs\": \"cell_type\", \"keep_original\": \"false\"}], \"output_format\": \"anndata_h5ad\", \"sanitize_varm\": \"false\", \"top_genes\": \"50\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.8.1+galaxy0",
+ "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"manipulate\": {\"function\": \"rename_categories\", \"__current_case__\": 3, \"key\": \"louvain\", \"categories\": \"DP-M4,DP-M3,DP-M1,T-mat,DN,DP-L,DP-M2,Macrophages\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "584bf7e3-05d7-4010-ba67-98375379c621",
+ "uuid": "cf6cc2d8-6ca7-4002-aee0-12010520bfe8",
+ "when": null,
"workflow_outputs": [
{
- "label": "Final cell annotated object",
- "output_name": "output_h5ad",
- "uuid": "a6d48df0-403f-4efc-a75f-9504a960884e"
+ "label": null,
+ "output_name": "anndata",
+ "uuid": "a547d735-3afe-43fa-ac21-9567af1b6de5"
}
]
},
- "41": {
+ "40": {
"annotation": "",
"content_id": "Cut1",
"errors": null,
- "id": 41,
+ "id": 40,
"input_connections": {
"input": {
- "id": 38,
+ "id": 37,
"output_name": "out_file1"
}
},
@@ -2051,8 +2069,8 @@
}
],
"position": {
- "left": 4468.2109375,
- "top": 1014.2890625
+ "left": 4468.000030517578,
+ "top": 993.0937194824219
},
"post_job_actions": {
"RenameDatasetActionout_file1": {
@@ -2065,25 +2083,26 @@
},
"tool_id": "Cut1",
"tool_state": "{\"columnList\": \"c1,c2,c3,c4,c11,c5,c6,c7,c8\", \"delimiter\": \"T\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.0.2",
+ "tool_version": null,
"type": "tool",
- "uuid": "45fddc4f-1b9d-4464-b08b-c502d4d05a30",
+ "uuid": "91bab6ee-a18f-4814-b4f4-e1d2be331318",
+ "when": null,
"workflow_outputs": [
{
"label": "Markers - cluster - named",
"output_name": "out_file1",
- "uuid": "0ee7f9b6-b065-4e26-93df-6e6e2fe458a9"
+ "uuid": "40c720f0-c09c-47d6-a16b-57bef9b6ddf2"
}
]
},
- "42": {
+ "41": {
"annotation": "",
"content_id": "Cut1",
"errors": null,
- "id": 42,
+ "id": 41,
"input_connections": {
"input": {
- "id": 39,
+ "id": 38,
"output_name": "out_file1"
}
},
@@ -2097,8 +2116,8 @@
}
],
"position": {
- "left": 4468.2109375,
- "top": 1199.2890625
+ "left": 4468.000030517578,
+ "top": 1178.0937194824219
},
"post_job_actions": {
"RenameDatasetActionout_file1": {
@@ -2111,34 +2130,30 @@
},
"tool_id": "Cut1",
"tool_state": "{\"columnList\": \"c1,c2,c3,c4,c11,c5,c6,c7,c8\", \"delimiter\": \"T\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.0.2",
+ "tool_version": null,
"type": "tool",
- "uuid": "995cfd57-925a-470e-879b-8d7eb619c67b",
+ "uuid": "031d1b26-b63b-4cf1-98e1-77d30db47eec",
+ "when": null,
"workflow_outputs": [
{
"label": "Markers - genotype - named",
"output_name": "out_file1",
- "uuid": "fdb88faa-9b76-4edb-b89b-427c098a473e"
+ "uuid": "38221cc7-e308-4240-83cd-cbee91093ae5"
}
]
},
- "43": {
+ "42": {
"annotation": "",
- "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9",
"errors": null,
- "id": 43,
+ "id": 42,
"input_connections": {
"input_obj_file": {
- "id": 40,
- "output_name": "output_h5ad"
+ "id": 39,
+ "output_name": "anndata"
}
},
- "inputs": [
- {
- "description": "runtime parameter for tool Scanpy PlotEmbed",
- "name": "input_obj_file"
- }
- ],
+ "inputs": [],
"label": null,
"name": "Scanpy PlotEmbed",
"outputs": [
@@ -2148,35 +2163,35 @@
}
],
"position": {
- "left": 4653.7109375,
- "top": 231.5
+ "left": 4653.500061035156,
+ "top": 210.32814025878906
},
"post_job_actions": {},
- "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0",
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9",
"tool_shed_repository": {
- "changeset_revision": "56d22aa6cb3b",
+ "changeset_revision": "35f6611fb8c3",
"name": "scanpy_plot_embed",
"owner": "ebi-gxa",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,log1p_total_counts,Hba-a1,cell_type\", \"components\": \"\", \"edges\": \"false\", \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": \"false\", \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"RuntimeValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": \"false\", \"use_raw\": \"false\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": "1.8.1+galaxy0",
+ "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type\", \"components\": \"\", \"edges\": false, \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": false, \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": false, \"use_raw\": false, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
"type": "tool",
- "uuid": "ff379bdf-e875-4803-baa0-b11bd71666db",
+ "uuid": "6185e50d-2359-47e4-9a65-73215705e21c",
+ "when": null,
"workflow_outputs": [
{
"label": null,
"output_name": "output_png",
- "uuid": "cb97c2f3-8e23-45d0-bc96-faf2f06b59d0"
+ "uuid": "c81c00cf-3087-4dee-8b1e-83e16db3b2af"
}
]
}
},
"tags": [
- "name:transcriptomics",
- "name:training",
- "name:singlecell"
+ "name:singlecell",
+ "name:training"
],
- "uuid": "3d42c837-d379-4f2f-bc4d-08d7b502afe6",
- "version": 7
+ "uuid": "a765a07e-1354-4c38-98a2-fe141e4871ed",
+ "version": 1
}
\ No newline at end of file
From 4ae58d1687de8467566a03f081f12dc4d156157b Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 14:40:42 +0100
Subject: [PATCH 17/31] Revert "FPE fixes"
This reverts commit f2d6314909ec8ac00139cc6253b41a0f7634a23e.
---
.../scrna-case_basic-pipeline/tutorial.md | 36 +-
...t_and_Explore_Single-cell_RNA-seq_Data.ga} | 861 +++++++++---------
...Single-cell-RNA-seq-Data-updated-test.yml} | 2 +-
3 files changed, 446 insertions(+), 453 deletions(-)
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga => CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga} (64%)
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml => Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml} (99%)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
index 5af33da235e0c6..3ecd8fdf93c4b0 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
@@ -808,26 +808,34 @@ The authors weren't interested in further annotation of the DP cells, so neither
> Annotating clusters
>
-> 1. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
-> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
-> - *"Change field names in AnnData observations"*
-> - {% icon galaxy-wf-new %} *"Insert Change field names in AnnData observations"*
-> - *"1: Change field names in AnnData observations"*
-> - *"Original name"*: `louvain`
-> - *"New name"*: `cell_type`
-> - *"Keep original"*: {% icon history-share %} `Yes`
-> - This makes a copy of the louvain column, which you can change without altering the original
->
-> 2. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
+> 1. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
> - {% icon param-file %} *"Annotated data matrix"*: `Final object`
> - *"Function to manipulate the object"*: `Rename categories of annotation`
> - *"Key for observations or variables annotation"*: `louvain`
> - *"Comma-separated list of new categories"*: `DP-M4,DP-M3,DP-M1,T-mat,DN,DP-L,DP-M2,Macrophages`
-> - Note that if you have a slightly different clustering, your list of categories might not match. You could have a different number of categories, or they could be in a different order.
+> - Hang on here, though. This unfortunately deletes the original cluster numbering. Just in case you might want this back, we can add that annotation back in.
+>
+> 2. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} with the following parameters:
+> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
+> - *"Copy observations (such as clusters)"*: {% icon history-share %} *Yes*
+> - **Keys from obs to copy**
+> - *"+ Insert Keys from obs to copy"*
+> - *"Key contains"*: `louvain`
+> - {% icon param-file %} *"AnnData objects with obs to copy"*: (output of **Manipulate AnnData** {% icon tool %})
+>
+> - You've added the new cell annotations in, now titled `louvain_0`. What, that's not good enough? You want to change the title as well? So be it.
+>
+> 3. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
+> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: (output of **AnnData Operations** {% icon tool %})
+> - **Change field names in AnnData observations**
+> - {% icon galaxy-wf-new %} *"+ Insert Change field names in AnnData observations"*
+> - **1: Change field names in AnnData observations**
+> - *"Original name"*: `louvain_0`
+> - *"New name"*: `cell_type`
>
-> 3. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
+> 4. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
> - Time to re-plot! {% icon time %} Feel free to re-run {% icon galaxy-refresh %} the **Scanpy PlotEmbed** tool {% icon tool %} on the new object plotting `cell_type` to speed this up. Otherwise...
-> 4. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
+> 5. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"Input object in AnnData/Loom format"*: `Final cell annotated object`
> - *"name of the embedding to plot"*: `umap`
> - *"color by attributes, comma separated texts"*: `sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type`
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
similarity index 64%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
index 99c6c10246ea7f..b806556141af9f 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
@@ -1,21 +1,8 @@
{
"a_galaxy_workflow": "true",
- "annotation": "",
- "creator": [
- {
- "class": "Person",
- "identifier": "0000-0002-8170-8806",
- "name": "Wendi Bacon"
- },
- {
- "class": "Person",
- "identifier": "0009-0001-2017-8805",
- "name": "Julia Jakiela"
- }
- ],
+ "annotation": "Updated tool versions Aug 24 2022",
"format-version": "0.1",
- "license": "CC-BY-4.0",
- "name": "Filter, Plot and Explore Single-cell RNA-seq Data",
+ "name": "CS3_Filter, Plot and Explore Single-cell RNA-seq Data",
"steps": {
"0": {
"annotation": "",
@@ -34,14 +21,13 @@
"outputs": [],
"position": {
"left": 0,
- "top": 715.0156402587891
+ "top": 736.1875
},
"tool_id": null,
"tool_state": "{\"optional\": false, \"tag\": null}",
"tool_version": null,
"type": "data_input",
- "uuid": "12249163-a3de-445f-95cd-a7a627da5076",
- "when": null,
+ "uuid": "60316d4a-07b0-4eea-a889-eef54798c5e0",
"workflow_outputs": []
},
"1": {
@@ -65,8 +51,8 @@
}
],
"position": {
- "left": 277.87506103515625,
- "top": 0
+ "left": 277.8984375,
+ "top": 21.0703125
},
"post_job_actions": {},
"tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
@@ -76,22 +62,21 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
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"output_name": "output_h5ad"
}
},
- "inputs": [
- {
- "description": "runtime parameter for tool AnnData Operations",
- "name": "copy_o"
- }
- ],
+ "inputs": [],
"label": null,
"name": "AnnData Operations",
"outputs": [
@@ -1893,42 +1871,41 @@
}
],
"position": {
- "left": 4301.99999609375,
- "top": 523.046875
+ "left": 4386.2109375,
+ "top": 257.1875
},
"post_job_actions": {},
- "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy91",
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0",
"tool_shed_repository": {
- "changeset_revision": "7ebc22f77d86",
+ "changeset_revision": "890fb06a2893",
"name": "anndata_ops",
"owner": "ebi-gxa",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"add_cell_metadata\": {\"default\": false, \"__current_case__\": 1}, \"copy_adata_to_raw\": false, \"copy_e\": {\"default\": false, \"__current_case__\": 1}, \"copy_l\": {\"default\": false, \"__current_case__\": 1}, \"copy_o\": {\"default\": true, \"__current_case__\": 0, \"obs_keys\": [{\"__index__\": 0, \"contains\": \"louvain\"}], \"obs_sources\": {\"__class__\": \"RuntimeValue\"}}, \"copy_r\": {\"default\": false, \"__current_case__\": 1}, \"copy_u\": {\"default\": false, \"__current_case__\": 1}, \"copy_x\": {\"default\": false, \"__current_case__\": 1}, \"field_unique\": null, \"gene_flags\": [], \"gene_symbols_field\": \"index\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"modifications\": [{\"__index__\": 0, \"from_obs\": \"louvain\", \"to_obs\": \"cell_type\", \"keep_original\": true, \"make_unique\": false}], \"output_format\": \"anndata_h5ad\", \"sanitize_varm\": false, \"top_genes\": \"50\", \"var_modifications\": [], \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"copy_adata_to_raw\": \"false\", \"copy_e\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_l\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_o\": {\"default\": \"true\", \"__current_case__\": 0, \"obs_keys\": [{\"__index__\": 0, \"contains\": \"louvain\"}], \"obs_sources\": {\"__class__\": \"ConnectedValue\"}}, \"copy_r\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_u\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_x\": {\"default\": \"false\", \"__current_case__\": 1}, \"gene_flags\": [], \"gene_symbols_field\": \"index\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"modifications\": [], \"output_format\": \"anndata_h5ad\", \"sanitize_varm\": \"false\", \"top_genes\": \"50\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.8.1+galaxy0",
"type": "tool",
- "uuid": "36ca1d92-979d-4856-a650-28ec0c315b4e",
- "when": null,
+ "uuid": "573bf376-2011-4572-ad91-84df828f1242",
"workflow_outputs": [
{
"label": null,
"output_name": "output_h5ad",
- "uuid": "e969159c-5d55-4429-b722-2bc18c9361c2"
+ "uuid": "50717627-47ed-40bc-bf18-17198416a57f"
}
]
},
- "37": {
+ "38": {
"annotation": "",
"content_id": "join1",
"errors": null,
- "id": 37,
+ "id": 38,
"input_connections": {
"input1": {
"id": 30,
"output_name": "output_tsv"
},
"input2": {
- "id": 35,
+ "id": 36,
"output_name": "var"
}
},
@@ -1942,36 +1919,35 @@
}
],
"position": {
- "left": 4190.000076293945,
- "top": 955.0937652587891
+ "left": 4190.2109375,
+ "top": 976.3046875
},
"post_job_actions": {},
"tool_id": "join1",
"tool_state": "{\"__input_ext\": \"tabular\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"field1\": \"4\", \"field2\": \"2\", \"fill_empty_columns\": {\"fill_empty_columns_switch\": \"no_fill\", \"__current_case__\": 0}, \"header\": \"-H\", \"input1\": {\"__class__\": \"ConnectedValue\"}, \"input2\": {\"__class__\": \"ConnectedValue\"}, \"partial\": \"-p\", \"unmatched\": \"-u\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_version": "2.1.3",
"type": "tool",
- "uuid": "865701b0-5ef2-4a42-b9d1-ce39423dc775",
- "when": null,
+ "uuid": "db6d5777-a3dd-467d-8541-91bb998e0e72",
"workflow_outputs": [
{
"label": null,
"output_name": "out_file1",
- "uuid": "ebddb6c4-a4a9-4ca2-b9ac-87796242b88d"
+ "uuid": "cb6967d5-7390-4d2e-b2c4-1d8a9e2d3c69"
}
]
},
- "38": {
+ "39": {
"annotation": "",
"content_id": "join1",
"errors": null,
- "id": 38,
+ "id": 39,
"input_connections": {
"input1": {
"id": 31,
"output_name": "output_tsv"
},
"input2": {
- "id": 35,
+ "id": 36,
"output_name": "var"
}
},
@@ -1985,77 +1961,83 @@
}
],
"position": {
- "left": 4190.000076293945,
- "top": 1140.0936889648438
+ "left": 4178.2109375,
+ "top": 1199.2890625
},
"post_job_actions": {},
"tool_id": "join1",
- "tool_state": "{\"__input_ext\": \"tabular\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"field1\": \"4\", \"field2\": \"2\", \"fill_empty_columns\": {\"fill_empty_columns_switch\": \"no_fill\", \"__current_case__\": 0}, \"header\": \"-H\", \"input1\": {\"__class__\": \"ConnectedValue\"}, \"input2\": {\"__class__\": \"ConnectedValue\"}, \"partial\": \"-p\", \"unmatched\": \"-u\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"field1\": \"4\", \"field2\": \"2\", \"fill_empty_columns\": {\"fill_empty_columns_switch\": \"no_fill\", \"__current_case__\": 0}, \"header\": \"-H\", \"input1\": {\"__class__\": \"ConnectedValue\"}, \"input2\": {\"__class__\": \"ConnectedValue\"}, \"partial\": \"-p\", \"unmatched\": \"-u\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "2.1.3",
"type": "tool",
- "uuid": "4381f3df-c621-4c92-8598-de5ee9c46a64",
- "when": null,
+ "uuid": "f4db0e7d-dfc8-4f77-bca0-997a0347304b",
"workflow_outputs": [
{
"label": null,
"output_name": "out_file1",
- "uuid": "87490b1e-f4b9-4ded-8751-c4eff7859b8c"
+ "uuid": "54cdb2bd-437b-47e4-90c1-e99e0b468574"
}
]
},
- "39": {
+ "40": {
"annotation": "",
- "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0",
"errors": null,
- "id": 39,
+ "id": 40,
"input_connections": {
- "input": {
- "id": 36,
+ "input_obj_file": {
+ "id": 37,
"output_name": "output_h5ad"
}
},
"inputs": [],
"label": null,
- "name": "Manipulate AnnData",
+ "name": "AnnData Operations",
"outputs": [
{
- "name": "anndata",
+ "name": "output_h5ad",
"type": "h5ad"
}
],
"position": {
- "left": 4178.84374609375,
- "top": 195.09375
+ "left": 4468.2109375,
+ "top": 0
},
- "post_job_actions": {},
- "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1",
+ "post_job_actions": {
+ "RenameDatasetActionoutput_h5ad": {
+ "action_arguments": {
+ "newname": "Final cell annotated object"
+ },
+ "action_type": "RenameDatasetAction",
+ "output_name": "output_h5ad"
+ }
+ },
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0",
"tool_shed_repository": {
- "changeset_revision": "3d748954434b",
- "name": "anndata_manipulate",
- "owner": "iuc",
+ "changeset_revision": "890fb06a2893",
+ "name": "anndata_ops",
+ "owner": "ebi-gxa",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"manipulate\": {\"function\": \"rename_categories\", \"__current_case__\": 3, \"key\": \"louvain\", \"categories\": \"DP-M4,DP-M3,DP-M1,T-mat,DN,DP-L,DP-M2,Macrophages\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"copy_adata_to_raw\": \"false\", \"copy_e\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_l\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_o\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_r\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_u\": {\"default\": \"false\", \"__current_case__\": 1}, \"copy_x\": {\"default\": \"false\", \"__current_case__\": 1}, \"gene_flags\": [], \"gene_symbols_field\": \"index\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"modifications\": [{\"__index__\": 0, \"from_obs\": \"louvain_0\", \"to_obs\": \"cell_type\", \"keep_original\": \"false\"}], \"output_format\": \"anndata_h5ad\", \"sanitize_varm\": \"false\", \"top_genes\": \"50\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.8.1+galaxy0",
"type": "tool",
- "uuid": "cf6cc2d8-6ca7-4002-aee0-12010520bfe8",
- "when": null,
+ "uuid": "584bf7e3-05d7-4010-ba67-98375379c621",
"workflow_outputs": [
{
- "label": null,
- "output_name": "anndata",
- "uuid": "a547d735-3afe-43fa-ac21-9567af1b6de5"
+ "label": "Final cell annotated object",
+ "output_name": "output_h5ad",
+ "uuid": "a6d48df0-403f-4efc-a75f-9504a960884e"
}
]
},
- "40": {
+ "41": {
"annotation": "",
"content_id": "Cut1",
"errors": null,
- "id": 40,
+ "id": 41,
"input_connections": {
"input": {
- "id": 37,
+ "id": 38,
"output_name": "out_file1"
}
},
@@ -2069,8 +2051,8 @@
}
],
"position": {
- "left": 4468.000030517578,
- "top": 993.0937194824219
+ "left": 4468.2109375,
+ "top": 1014.2890625
},
"post_job_actions": {
"RenameDatasetActionout_file1": {
@@ -2083,26 +2065,25 @@
},
"tool_id": "Cut1",
"tool_state": "{\"columnList\": \"c1,c2,c3,c4,c11,c5,c6,c7,c8\", \"delimiter\": \"T\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_version": "1.0.2",
"type": "tool",
- "uuid": "91bab6ee-a18f-4814-b4f4-e1d2be331318",
- "when": null,
+ "uuid": "45fddc4f-1b9d-4464-b08b-c502d4d05a30",
"workflow_outputs": [
{
"label": "Markers - cluster - named",
"output_name": "out_file1",
- "uuid": "40c720f0-c09c-47d6-a16b-57bef9b6ddf2"
+ "uuid": "0ee7f9b6-b065-4e26-93df-6e6e2fe458a9"
}
]
},
- "41": {
+ "42": {
"annotation": "",
"content_id": "Cut1",
"errors": null,
- "id": 41,
+ "id": 42,
"input_connections": {
"input": {
- "id": 38,
+ "id": 39,
"output_name": "out_file1"
}
},
@@ -2116,8 +2097,8 @@
}
],
"position": {
- "left": 4468.000030517578,
- "top": 1178.0937194824219
+ "left": 4468.2109375,
+ "top": 1199.2890625
},
"post_job_actions": {
"RenameDatasetActionout_file1": {
@@ -2130,30 +2111,34 @@
},
"tool_id": "Cut1",
"tool_state": "{\"columnList\": \"c1,c2,c3,c4,c11,c5,c6,c7,c8\", \"delimiter\": \"T\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_version": "1.0.2",
"type": "tool",
- "uuid": "031d1b26-b63b-4cf1-98e1-77d30db47eec",
- "when": null,
+ "uuid": "995cfd57-925a-470e-879b-8d7eb619c67b",
"workflow_outputs": [
{
"label": "Markers - genotype - named",
"output_name": "out_file1",
- "uuid": "38221cc7-e308-4240-83cd-cbee91093ae5"
+ "uuid": "fdb88faa-9b76-4edb-b89b-427c098a473e"
}
]
},
- "42": {
+ "43": {
"annotation": "",
- "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0",
"errors": null,
- "id": 42,
+ "id": 43,
"input_connections": {
"input_obj_file": {
- "id": 39,
- "output_name": "anndata"
+ "id": 40,
+ "output_name": "output_h5ad"
}
},
- "inputs": [],
+ "inputs": [
+ {
+ "description": "runtime parameter for tool Scanpy PlotEmbed",
+ "name": "input_obj_file"
+ }
+ ],
"label": null,
"name": "Scanpy PlotEmbed",
"outputs": [
@@ -2163,35 +2148,35 @@
}
],
"position": {
- "left": 4653.500061035156,
- "top": 210.32814025878906
+ "left": 4653.7109375,
+ "top": 231.5
},
"post_job_actions": {},
- "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9",
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0",
"tool_shed_repository": {
- "changeset_revision": "35f6611fb8c3",
+ "changeset_revision": "56d22aa6cb3b",
"name": "scanpy_plot_embed",
"owner": "ebi-gxa",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type\", \"components\": \"\", \"edges\": false, \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": false, \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": false, \"use_raw\": false, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,log1p_total_counts,Hba-a1,cell_type\", \"components\": \"\", \"edges\": \"false\", \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": \"false\", \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"RuntimeValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": \"false\", \"use_raw\": \"false\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.8.1+galaxy0",
"type": "tool",
- "uuid": "6185e50d-2359-47e4-9a65-73215705e21c",
- "when": null,
+ "uuid": "ff379bdf-e875-4803-baa0-b11bd71666db",
"workflow_outputs": [
{
"label": null,
"output_name": "output_png",
- "uuid": "c81c00cf-3087-4dee-8b1e-83e16db3b2af"
+ "uuid": "cb97c2f3-8e23-45d0-bc96-faf2f06b59d0"
}
]
}
},
"tags": [
- "name:singlecell",
- "name:training"
+ "name:transcriptomics",
+ "name:training",
+ "name:singlecell"
],
- "uuid": "a765a07e-1354-4c38-98a2-fe141e4871ed",
- "version": 1
+ "uuid": "3d42c837-d379-4f2f-bc4d-08d7b502afe6",
+ "version": 7
}
\ No newline at end of file
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
similarity index 99%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
index 03b284b4b4d86f..9a5fefcafa1e26 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
@@ -1,4 +1,4 @@
-- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data
+- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated
job:
Mito-counted AnnData:
class: File
From b3142ec32dc2325026e33ecfdc5ddc289a7d788e Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 14:41:32 +0100
Subject: [PATCH 18/31] Update
Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
---
.../Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
index 03b284b4b4d86f..9a5fefcafa1e26 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
@@ -1,4 +1,4 @@
-- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data
+- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated
job:
Mito-counted AnnData:
class: File
From 264203bc12e1e066d4c46478aa2f5fe934b184d6 Mon Sep 17 00:00:00 2001
From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com>
Date: Fri, 13 Oct 2023 14:42:03 +0100
Subject: [PATCH 19/31] Revert "Merge branch 'faq_common_sc_text' of
https://github.com/nomadscientist/training-material into faq_common_sc_text"
This reverts commit 486767ffc3402c6f1f892859ec997ee972d1c12c, reversing
changes made to 4ae58d1687de8467566a03f081f12dc4d156157b.
---
.../scrna-case_basic-pipeline/tutorial.md | 36 +-
...t_and_Explore_Single-cell_RNA-seq_Data.ga} | 861 +++++++++---------
...Single-cell-RNA-seq-Data-updated-test.yml} | 2 +-
3 files changed, 446 insertions(+), 453 deletions(-)
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga => CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga} (64%)
rename topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/{Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml => Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml} (99%)
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
index 5af33da235e0c6..3ecd8fdf93c4b0 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md
@@ -808,26 +808,34 @@ The authors weren't interested in further annotation of the DP cells, so neither
> Annotating clusters
>
-> 1. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
-> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
-> - *"Change field names in AnnData observations"*
-> - {% icon galaxy-wf-new %} *"Insert Change field names in AnnData observations"*
-> - *"1: Change field names in AnnData observations"*
-> - *"Original name"*: `louvain`
-> - *"New name"*: `cell_type`
-> - *"Keep original"*: {% icon history-share %} `Yes`
-> - This makes a copy of the louvain column, which you can change without altering the original
->
-> 2. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
+> 1. {% tool [Manipulate AnnData](toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1) %} with the following parameters:
> - {% icon param-file %} *"Annotated data matrix"*: `Final object`
> - *"Function to manipulate the object"*: `Rename categories of annotation`
> - *"Key for observations or variables annotation"*: `louvain`
> - *"Comma-separated list of new categories"*: `DP-M4,DP-M3,DP-M1,T-mat,DN,DP-L,DP-M2,Macrophages`
-> - Note that if you have a slightly different clustering, your list of categories might not match. You could have a different number of categories, or they could be in a different order.
+> - Hang on here, though. This unfortunately deletes the original cluster numbering. Just in case you might want this back, we can add that annotation back in.
+>
+> 2. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} with the following parameters:
+> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: `Final object`
+> - *"Copy observations (such as clusters)"*: {% icon history-share %} *Yes*
+> - **Keys from obs to copy**
+> - *"+ Insert Keys from obs to copy"*
+> - *"Key contains"*: `louvain`
+> - {% icon param-file %} *"AnnData objects with obs to copy"*: (output of **Manipulate AnnData** {% icon tool %})
+>
+> - You've added the new cell annotations in, now titled `louvain_0`. What, that's not good enough? You want to change the title as well? So be it.
+>
+> 3. {% tool [AnnData Operations](toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy0) %} {% icon tool %} with the following parameters:
+> - {% icon param-file %} *"Input object in hdf5 AnnData format"*: (output of **AnnData Operations** {% icon tool %})
+> - **Change field names in AnnData observations**
+> - {% icon galaxy-wf-new %} *"+ Insert Change field names in AnnData observations"*
+> - **1: Change field names in AnnData observations**
+> - *"Original name"*: `louvain_0`
+> - *"New name"*: `cell_type`
>
-> 3. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
+> 4. **Rename** {% icon galaxy-pencil %} output h5ad `Final cell annotated object`
> - Time to re-plot! {% icon time %} Feel free to re-run {% icon galaxy-refresh %} the **Scanpy PlotEmbed** tool {% icon tool %} on the new object plotting `cell_type` to speed this up. Otherwise...
-> 4. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
+> 5. {% tool [Scanpy PlotEmbed](toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"Input object in AnnData/Loom format"*: `Final cell annotated object`
> - *"name of the embedding to plot"*: `umap`
> - *"color by attributes, comma separated texts"*: `sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type`
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
similarity index 64%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
index 99c6c10246ea7f..b806556141af9f 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/CS3_Filter,_Plot_and_Explore_Single-cell_RNA-seq_Data.ga
@@ -1,21 +1,8 @@
{
"a_galaxy_workflow": "true",
- "annotation": "",
- "creator": [
- {
- "class": "Person",
- "identifier": "0000-0002-8170-8806",
- "name": "Wendi Bacon"
- },
- {
- "class": "Person",
- "identifier": "0009-0001-2017-8805",
- "name": "Julia Jakiela"
- }
- ],
+ "annotation": "Updated tool versions Aug 24 2022",
"format-version": "0.1",
- "license": "CC-BY-4.0",
- "name": "Filter, Plot and Explore Single-cell RNA-seq Data",
+ "name": "CS3_Filter, Plot and Explore Single-cell RNA-seq Data",
"steps": {
"0": {
"annotation": "",
@@ -34,14 +21,13 @@
"outputs": [],
"position": {
"left": 0,
- "top": 715.0156402587891
+ "top": 736.1875
},
"tool_id": null,
"tool_state": "{\"optional\": false, \"tag\": null}",
"tool_version": null,
"type": "data_input",
- "uuid": "12249163-a3de-445f-95cd-a7a627da5076",
- "when": null,
+ "uuid": "60316d4a-07b0-4eea-a889-eef54798c5e0",
"workflow_outputs": []
},
"1": {
@@ -65,8 +51,8 @@
}
],
"position": {
- "left": 277.87506103515625,
- "top": 0
+ "left": 277.8984375,
+ "top": 21.0703125
},
"post_job_actions": {},
"tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
@@ -76,22 +62,21 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"__input_ext\": \"h5ad\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"obs\", \"__current_case__\": 3}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "0.7.5+galaxy1",
"type": "tool",
- "uuid": "71e5aa83-23a9-467b-bcf8-50dfe4a98331",
- "when": null,
+ "uuid": "99ffbf79-3be8-4905-b978-e56b02327314",
"workflow_outputs": [
{
"label": null,
"output_name": "obs",
- "uuid": "a47dc402-352e-4878-9b0e-da86ca690f92"
+ "uuid": "6e2bd8b0-8203-4dfe-9c28-054d863bd277"
}
]
},
"2": {
"annotation": "",
- "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy0",
"errors": null,
"id": 2,
"input_connections": {
@@ -110,8 +95,8 @@
}
],
"position": {
- "left": 277.87506103515625,
- "top": 217.06249237060547
+ "left": 277.8984375,
+ "top": 238.2421875
},
"post_job_actions": {
"RenameDatasetActionoutput_h5ad": {
@@ -122,23 +107,22 @@
"output_name": "output_h5ad"
}
},
- "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9",
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy0",
"tool_shed_repository": {
- "changeset_revision": "e9283529cba1",
+ "changeset_revision": "55ccc0a121bc",
"name": "scanpy_filter_cells",
"owner": "ebi-gxa",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"categories\": [], \"export_mtx\": false, \"force_recalc\": false, \"gene_name\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"output_format\": \"anndata_h5ad\", \"parameters\": [{\"__index__\": 0, \"name\": \"log1p_n_genes_by_counts\", \"min\": \"5.7\", \"max\": \"20.0\"}], \"save_layer\": null, \"save_raw\": false, \"subsets\": [], \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"categories\": [], \"export_mtx\": \"false\", \"force_recalc\": \"false\", \"gene_name\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"output_format\": \"anndata_h5ad\", \"parameters\": [{\"__index__\": 0, \"name\": \"log1p_n_genes_by_counts\", \"min\": \"5.7\", \"max\": \"20.0\"}], \"save_layer\": null, \"save_raw\": \"false\", \"subsets\": [], \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.8.1+galaxy0",
"type": "tool",
- "uuid": "2b0750ea-ffb2-436a-91b3-2f0f796f18d7",
- "when": null,
+ "uuid": "ab02dab9-1c72-4987-929c-6b67baae1e6d",
"workflow_outputs": [
{
"label": "Genes-filtered Object",
"output_name": "output_h5ad",
- "uuid": "c132bfef-6484-45ab-b634-8e25e408deea"
+ "uuid": "08175d7f-f4f4-413c-ad86-f59587ff692e"
}
]
},
@@ -163,8 +147,8 @@
}
],
"position": {
- "left": 277.87506103515625,
- "top": 413.0937194824219
+ "left": 277.8984375,
+ "top": 434.28125
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -182,16 +166,15 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_total_counts\", \"y\": \"log1p_n_genes_by_counts\", \"color\": \"pct_counts_mito\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": false, \"sort_order\": true, \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": true, \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_total_counts\", \"y\": \"log1p_n_genes_by_counts\", \"color\": \"pct_counts_mito\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": \"false\", \"sort_order\": \"true\", \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": \"true\", \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.7.1+galaxy1",
"type": "tool",
- "uuid": "95975f35-24be-4e65-8830-ad18b5fa7943",
- "when": null,
+ "uuid": "767da31e-dc80-4d11-9f8e-8b1589029dcc",
"workflow_outputs": [
{
"label": "Scatter - genes x UMIs",
"output_name": "out_png",
- "uuid": "58e53e50-4bf8-4980-8f74-40198c29bbb7"
+ "uuid": "bfc499ee-630a-498b-9be6-696d9bb78837"
}
]
},
@@ -216,8 +199,8 @@
}
],
"position": {
- "left": 277.87506103515625,
- "top": 567.0468902587891
+ "left": 277.8984375,
+ "top": 588.25
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -235,16 +218,15 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_n_genes_by_counts\", \"y\": \"pct_counts_mito\", \"color\": \"\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": false, \"sort_order\": true, \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": true, \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.scatter\", \"__current_case__\": 0, \"type\": {\"type\": \"xy\", \"__current_case__\": 0, \"x\": \"log1p_n_genes_by_counts\", \"y\": \"pct_counts_mito\", \"color\": \"\", \"layers\": {\"use_layers\": \"false\", \"__current_case__\": 1}}, \"use_raw\": \"false\", \"sort_order\": \"true\", \"groups\": \"\", \"plot\": {\"components\": [], \"projection\": \"2d\", \"legend_loc\": \"right margin\", \"legend_fontsize\": null, \"legend_fontweight\": \"normal\", \"color_map\": \"None\", \"palette\": \"default\", \"frameon\": \"true\", \"size\": null, \"title\": \"\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.7.1+galaxy1",
"type": "tool",
- "uuid": "984cec24-7821-4fe6-868c-eaca648439b0",
- "when": null,
+ "uuid": "ad0b1195-4bb2-46be-bb8a-8fd5de416372",
"workflow_outputs": [
{
"label": "Scatter - mito x genes",
"output_name": "out_png",
- "uuid": "5976a26f-7e4a-4af4-bda4-0dd0dc7c8ef8"
+ "uuid": "f2c78ef3-7d31-4930-954c-0133cce27a41"
}
]
},
@@ -269,8 +251,8 @@
}
],
"position": {
- "left": 278.98952554536163,
- "top": 721.0843561275927
+ "left": 277.8984375,
+ "top": 742.28125
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -288,16 +270,15 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"genotype\", \"log\": false, \"use_raw\": false, \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"genotype\", \"log\": \"false\", \"use_raw\": \"false\", \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.7.1+galaxy1",
"type": "tool",
- "uuid": "0fe5d1b1-9eff-4043-98b1-7ecdd85dafac",
- "when": null,
+ "uuid": "a6a5b2f9-9765-4f5d-b4cf-7c513b8eed3c",
"workflow_outputs": [
{
"label": "Violin - genotype - log",
"output_name": "out_png",
- "uuid": "06c5979a-2e2e-4030-9c5b-adfafd85f7a7"
+ "uuid": "348818e6-9def-41fd-a390-6f8525c57cd8"
}
]
},
@@ -322,8 +303,8 @@
}
],
"position": {
- "left": 277.87506103515625,
- "top": 875.0937652587891
+ "left": 277.8984375,
+ "top": 896.3046875
},
"post_job_actions": {
"RenameDatasetActionout_png": {
@@ -341,16 +322,15 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": false}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"batch\", \"log\": false, \"use_raw\": false, \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"adata\": {\"__class__\": \"ConnectedValue\"}, \"advanced_common\": {\"show_log\": \"false\"}, \"format\": \"png\", \"method\": {\"method\": \"pl.violin\", \"__current_case__\": 3, \"key_variables\": {\"type\": \"custom\", \"__current_case__\": 2, \"keys\": \"log1p_total_counts,log1p_n_genes_by_counts,pct_counts_mito\"}, \"groupby\": \"batch\", \"log\": \"false\", \"use_raw\": \"false\", \"violin_plot\": {\"stripplot\": {\"stripplot\": \"True\", \"__current_case__\": 0, \"jitter\": {\"jitter\": \"True\", \"__current_case__\": 0, \"size\": \"1.0\"}}, \"multi_panel\": {\"multi_panel\": \"False\", \"__current_case__\": 1}, \"scale\": \"width\"}, \"xlabel\": \"\", \"rotation\": null, \"seaborn_violinplot\": {\"bw\": \"scott\", \"orient\": null, \"linewidth\": \"0.0\", \"color\": \"AliceBlue\", \"saturation\": \"0.75\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.7.1+galaxy1",
"type": "tool",
- "uuid": "8ee0819d-d8a7-4a08-a3bf-9431a86ae9fa",
- "when": null,
+ "uuid": "a6d8ecf9-1510-4c1a-8665-ddf25b0ca395",
"workflow_outputs": [
{
"label": "Violin - batch - log",
"output_name": "out_png",
- "uuid": "e78d661e-c014-4fad-91ef-af4cd99877c5"
+ "uuid": "844f5e7c-78c8-4f28-8e15-cea35ada8fef"
}
]
},
@@ -375,8 +355,8 @@
}
],
"position": {
- "left": 277.8749630368968,
- "top": 1008.0844487787456
+ "left": 277.8984375,
+ "top": 1029.3046875
},
"post_job_actions": {},
"tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1",
@@ -386,16 +366,15 @@
"owner": "iuc",
"tool_shed": "toolshed.g2.bx.psu.edu"
},
- "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"var\", \"__current_case__\": 4}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"__input_ext\": \"h5ad\", \"__workflow_invocation_uuid__\": \"190c9dc088ac11eb8307001e67d2ec02\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"inspect\": {\"info\": \"var\", \"__current_case__\": 4}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "0.7.5+galaxy1",
"type": "tool",
- "uuid": "1a0e6ed5-2a34-46bb-a028-8a7e7859ed1d",
- "when": null,
+ "uuid": "9445c5ea-8c75-48f2-b7a1-fd0e43c625c7",
"workflow_outputs": [
{
"label": null,
"output_name": "var",
- "uuid": "412e54d9-d405-430b-b75b-e748237b8c1f"
+ "uuid": "ba910718-a539-4b77-b3e8-087711e13eaf"
}
]
},
@@ -420,8 +399,8 @@
}
],
"position": {
- "left": 279.20030309822187,
- "top": 1246.0718715988953
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- "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,Hba-a1,log1p_total_counts,cell_type\", \"components\": \"\", \"edges\": false, \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": false, \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"ConnectedValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": false, \"use_raw\": false, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
- "tool_version": null,
+ "tool_state": "{\"basis\": \"umap\", \"color_by\": \"sex,batch,genotype,Il2ra,Cd8b1,Cd8a,Cd4,Itm2a,Aif1,log1p_total_counts,Hba-a1,cell_type\", \"components\": \"\", \"edges\": \"false\", \"edges_color\": \"\", \"edges_width\": \"0.1\", \"fig_dpi\": \"80\", \"fig_fontsize\": \"10\", \"fig_frame\": \"false\", \"fig_size\": \"4,4\", \"fig_title\": \"\", \"gene_symbols_field\": \"Symbol\", \"groups\": \"\", \"input_format\": \"anndata\", \"input_obj_file\": {\"__class__\": \"RuntimeValue\"}, \"layer\": \"\", \"legend_fontsize\": \"15\", \"legend_loc\": \"right margin\", \"neighbors_key\": \"\", \"point_size\": null, \"projection\": \"2d\", \"sort_order\": \"false\", \"use_raw\": \"false\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.8.1+galaxy0",
"type": "tool",
- "uuid": "6185e50d-2359-47e4-9a65-73215705e21c",
- "when": null,
+ "uuid": "ff379bdf-e875-4803-baa0-b11bd71666db",
"workflow_outputs": [
{
"label": null,
"output_name": "output_png",
- "uuid": "c81c00cf-3087-4dee-8b1e-83e16db3b2af"
+ "uuid": "cb97c2f3-8e23-45d0-bc96-faf2f06b59d0"
}
]
}
},
"tags": [
- "name:singlecell",
- "name:training"
+ "name:transcriptomics",
+ "name:training",
+ "name:singlecell"
],
- "uuid": "a765a07e-1354-4c38-98a2-fe141e4871ed",
- "version": 1
+ "uuid": "3d42c837-d379-4f2f-bc4d-08d7b502afe6",
+ "version": 7
}
\ No newline at end of file
diff --git a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
similarity index 99%
rename from topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
rename to topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
index 03b284b4b4d86f..9a5fefcafa1e26 100644
--- a/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-test.yml
+++ b/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated-test.yml
@@ -1,4 +1,4 @@
-- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data
+- doc: Test outline for Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated
job:
Mito-counted AnnData:
class: File
From 8de2f4b02a2e8b346dc02c94630104bf6e5cbb32 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Fri, 13 Oct 2023 14:30:30 -0400
Subject: [PATCH 20/31] Updated 2 workflows and tutorials to use the latest
version of Galaxy-ML
---
topics/statistics/tutorials/FNN/tutorial.md | 10 +-
.../tutorials/FNN/workflows/Intro_To_FNN.ga | 508 ------------------
.../FNN/workflows/Intro_To_FNN_v1.0.10.0.ga | 341 ++++++++++++
topics/statistics/tutorials/RNN/tutorial.md | 10 +-
.../tutorials/RNN/workflows/Intro_To_RNN.ga | 466 ----------------
.../RNN/workflows/Intro_To_RNN_v1.0.10.0.ga | 368 +++++++++++++
6 files changed, 719 insertions(+), 984 deletions(-)
delete mode 100644 topics/statistics/tutorials/FNN/workflows/Intro_To_FNN.ga
create mode 100644 topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
delete mode 100644 topics/statistics/tutorials/RNN/workflows/Intro_To_RNN.ga
create mode 100644 topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
diff --git a/topics/statistics/tutorials/FNN/tutorial.md b/topics/statistics/tutorials/FNN/tutorial.md
index 8d2f99d60308c9..22c0e9a6aace4c 100644
--- a/topics/statistics/tutorials/FNN/tutorial.md
+++ b/topics/statistics/tutorials/FNN/tutorial.md
@@ -339,7 +339,7 @@ dataset has 723 training examples, and our test dataset has 242 test examples. I
> Model config
>
-> - {% tool [Create a deep learning model architecture](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_config/keras_model_config/0.5.0) %}
+> - {% tool [Create a deep learning model architecture](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_config/keras_model_config/1.0.10.0) %}
> - *"Select keras model type"*: `sequential`
> - *"input_shape"*: `(5,)`
> - In *"LAYER"*:
@@ -366,7 +366,7 @@ layers use ReLU activation function. The model config can be downloaded as a JSO
> Model builder (Optimizer, loss function, and fit parameters)
>
-> - {% tool [Create deep learning model](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_builder/keras_model_builder/0.5.0) %}
+> - {% tool [Create deep learning model](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_builder/keras_model_builder/1.0.10.0) %}
> - *"Choose a building mode"*: `Build a training model`
> - *"Select the dataset containing model configuration"*: Select the *Keras Model Config* from the previous step.
> - *"Do classification or regression?"*: `KerasGRegressor`
@@ -391,7 +391,7 @@ batch_size decides the size of this subset (which we set to 50). The model build
> Training the model
>
-> - {% tool [Deep learning training and evaluation](toolshed.g2.bx.psu.edu/repos/bgruening/keras_train_and_eval/keras_train_and_eval/1.0.8.3) %}
+> - {% tool [Deep learning training and evaluation](toolshed.g2.bx.psu.edu/repos/bgruening/keras_train_and_eval/keras_train_and_eval/1.0.10.0) %}
> - *"Select a scheme"*: `Train and Validate`
> - *"Choose the dataset containing pipeline/estimator object"*: Select the *Keras Model Builder* from the previous step.
> - *"Select input type:"*: `tabular data`
@@ -406,14 +406,14 @@ batch_size decides the size of this subset (which we set to 50). The model build
>
{: .hands_on}
-The training step generates 3 datasets. 1) accuracy of the trained model, 2) the trained model, downloadable as a zip file, and 3) the trained
+The training step generates 2 datasets. 1) accuracy of the trained model, 2) the trained model, downloadable as a zip file, and 3) the trained
model weights, downloadable as an hdf5 file. These files are needed for prediction in the next step.
## Model Prediction
> Testing the model
>
-> - {% tool [Model Prediction](toolshed.g2.bx.psu.edu/repos/bgruening/model_prediction/model_prediction/1.0.8.3) %}
+> - {% tool [Model Prediction](toolshed.g2.bx.psu.edu/repos/bgruening/model_prediction/model_prediction/1.0.10.0) %}
> - *"Choose the dataset containing pipeline/estimator object"* : Select the trained model from the previous step.
> - *"Choose the dataset containing weights for the estimator above"* : Select the trained model weights from the previous step.
> - *"Select invocation method"*: `predict`
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN.ga b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN.ga
deleted file mode 100644
index f6a349d346bcd5..00000000000000
--- a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN.ga
+++ /dev/null
@@ -1,508 +0,0 @@
-{
- "a_galaxy_workflow": "true",
- "annotation": "Introduction to feedforward neural networks (FNN)",
- "format-version": "0.1",
- "name": "Intro_To_FNN",
- "steps": {
- "0": {
- "annotation": "",
- "content_id": null,
- "errors": null,
- "id": 0,
- "input_connections": {},
- "inputs": [
- {
- "description": "",
- "name": "X_train"
- }
- ],
- "label": "X_train",
- "name": "Input dataset",
- "outputs": [],
- "position": {
- "bottom": 254.70170211791992,
- "height": 61.73295211791992,
- "left": 392.9829406738281,
- "right": 592.9829406738281,
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- "width": 200,
- "x": 392.9829406738281,
- "y": 192.96875
- },
- "tool_id": null,
- "tool_state": "{\"optional\": false, \"tag\": null}",
- "tool_version": null,
- "type": "data_input",
- "uuid": "478ba9f7-22f6-4615-aec6-ddad97da39d9",
- "workflow_outputs": [
- {
- "label": null,
- "output_name": "output",
- "uuid": "f01fb19d-e816-48dc-b4e3-509f159fe0d6"
- }
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- },
- "1": {
- "annotation": "",
- "content_id": null,
- "errors": null,
- "id": 1,
- "input_connections": {},
- "inputs": [
- {
- "description": "",
- "name": "y_train"
- }
- ],
- "label": "y_train",
- "name": "Input dataset",
- "outputs": [],
- "position": {
- "bottom": 374.7301139831543,
- "height": 61.73295211791992,
- "left": 392.9829406738281,
- "right": 592.9829406738281,
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- "width": 200,
- "x": 392.9829406738281,
- "y": 312.9971618652344
- },
- "tool_id": null,
- "tool_state": "{\"optional\": false, \"tag\": null}",
- "tool_version": null,
- "type": "data_input",
- "uuid": "1168c128-8c62-4ee1-8c19-3c8ac839cf93",
- "workflow_outputs": [
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- "label": null,
- "output_name": "output",
- "uuid": "209b92da-d490-4e4d-a881-ce3b755fce35"
- }
- ]
- },
- "2": {
- "annotation": "",
- "content_id": null,
- "errors": null,
- "id": 2,
- "input_connections": {},
- "inputs": [
- {
- "description": "",
- "name": "X_test"
- }
- ],
- "label": "X_test",
- "name": "Input dataset",
- "outputs": [],
- "position": {
- "bottom": 494.71589279174805,
- "height": 61.73295211791992,
- "left": 392.9829406738281,
- "right": 592.9829406738281,
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- "width": 200,
- "x": 392.9829406738281,
- "y": 432.9829406738281
- },
- "tool_id": null,
- "tool_state": "{\"optional\": false, \"tag\": null}",
- "tool_version": null,
- "type": "data_input",
- "uuid": "d89f919d-330a-4c88-959e-4e39d1d86373",
- "workflow_outputs": [
- {
- "label": null,
- "output_name": "output",
- "uuid": "92fa6af3-d4b1-41e6-bad3-b498abf14e8d"
- }
- ]
- },
- "3": {
- "annotation": "",
- "content_id": null,
- "errors": null,
- "id": 3,
- "input_connections": {},
- "inputs": [
- {
- "description": "",
- "name": "y_test"
- }
- ],
- "label": "y_test",
- "name": "Input dataset",
- "outputs": [],
- "position": {
- "bottom": 614.7300834655762,
- "height": 61.73295211791992,
- "left": 392.9829406738281,
- "right": 592.9829406738281,
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- "width": 200,
- "x": 392.9829406738281,
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- "tool_id": null,
- "tool_state": "{\"optional\": false, \"tag\": null}",
- "tool_version": null,
- "type": "data_input",
- "uuid": "1e3f710b-8098-4847-aed0-f21eceb7029d",
- "workflow_outputs": [
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- "label": null,
- "output_name": "output",
- "uuid": "65dae08e-33a0-4576-af09-2507dcd35ccc"
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- "errors": null,
- "id": 4,
- "input_connections": {},
- "inputs": [],
- "label": null,
- "name": "Create a deep learning model architecture",
- "outputs": [
- {
- "name": "outfile",
- "type": "json"
- }
- ],
- "position": {
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- "owner": "bgruening",
- "tool_shed": "toolshed.g2.bx.psu.edu"
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- "tool_state": "{\"model_selection\": {\"model_type\": \"sequential\", \"__current_case__\": 0, \"input_shape\": \"(5, )\", \"layers\": [{\"__index__\": 0, \"layer_selection\": {\"layer_type\": \"Dense\", \"__current_case__\": 0, \"units\": \"12\", \"activation\": \"relu\", \"kwargs\": \"\"}}, {\"__index__\": 1, \"layer_selection\": {\"layer_type\": \"Dense\", \"__current_case__\": 0, \"units\": \"8\", \"activation\": \"relu\", \"kwargs\": \"\"}}, {\"__index__\": 2, \"layer_selection\": {\"layer_type\": \"Dense\", \"__current_case__\": 0, \"units\": \"1\", \"activation\": \"linear\", \"kwargs\": \"\"}}]}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
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- "id": 5,
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- "mode_selection|infile_json": {
- "id": 4,
- "output_name": "outfile"
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- "inputs": [
- {
- "description": "runtime parameter for tool Create deep learning model",
- "name": "mode_selection"
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- ],
- "label": null,
- "name": "Create deep learning model",
- "outputs": [
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- {
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diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
new file mode 100644
index 00000000000000..1e34c50a9bbb34
--- /dev/null
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
@@ -0,0 +1,341 @@
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+ "top": 250
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+ },
+ "inputs": [],
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+ "type": "html"
+ },
+ {
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+ "tool_version": null,
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+}
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diff --git a/topics/statistics/tutorials/RNN/tutorial.md b/topics/statistics/tutorials/RNN/tutorial.md
index ece79a8dd04f39..3fe444ffde29a2 100644
--- a/topics/statistics/tutorials/RNN/tutorial.md
+++ b/topics/statistics/tutorials/RNN/tutorial.md
@@ -259,7 +259,7 @@ and plot the confusion matrix.
> Model config
>
-> - {% tool [Create a deep learning model architecture](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_config/keras_model_config/0.5.0) %}
+> - {% tool [Create a deep learning model architecture](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_config/keras_model_config/1.0.10.0) %}
> - *"Select keras model type"*: `sequential`
> - *"input_shape"*: `(500,)`
> - In *"LAYER"*:
@@ -288,7 +288,7 @@ and anything less than 0.5 a negative one. The model config can be downloaded as
> Model builder (Optimizer, loss function, and fit parameters)
>
-> - {% tool [Create deep learning model](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_builder/keras_model_builder/0.5.0) %}
+> - {% tool [Create deep learning model](toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_builder/keras_model_builder/1.0.10.0) %}
> - *"Choose a building mode"*: `Build a training model`
> - *"Select the dataset containing model configuration"*: Select the *Keras Model Config* from the previous step.
> - *"Do classification or regression?"*: `KerasGClassifier`
@@ -313,7 +313,7 @@ The model builder can be downloaded as a zip file.
> Training the model
>
-> - {% tool [Deep learning training and evaluation](toolshed.g2.bx.psu.edu/repos/bgruening/keras_train_and_eval/keras_train_and_eval/1.0.8.3) %}
+> - {% tool [Deep learning training and evaluation](toolshed.g2.bx.psu.edu/repos/bgruening/keras_train_and_eval/keras_train_and_eval/1.0.10.0) %}
> - *"Select a scheme"*: `Train and Validate`
> - *"Choose the dataset containing pipeline/estimator object"*: Select the *Keras Model Builder* from the previous step.
> - *"Select input type:"*: `tabular data`
@@ -333,7 +333,7 @@ model weights, downloadable as an hdf5 file. These files are needed for predicti
> Testing the model
>
-> - {% tool [Model Prediction](toolshed.g2.bx.psu.edu/repos/bgruening/model_prediction/model_prediction/1.0.8.3) %}
+> - {% tool [Model Prediction](toolshed.g2.bx.psu.edu/repos/bgruening/model_prediction/model_prediction/1.0.10.0) %}
> - *"Choose the dataset containing pipeline/estimator object"* : Select the trained model from the previous step.
> - *"Choose the dataset containing weights for the estimator above"* : Select the trained model weights from the previous step.
> - *"Select invocation method"*: `predict`
@@ -351,7 +351,7 @@ the test dataset.
> Creating the confusion matrix
>
-> - {% tool [Machine Learning Visualization Extension](toolshed.g2.bx.psu.edu/repos/bgruening/ml_visualization_ex/ml_visualization_ex/1.0.8.3) %}
+> - {% tool [Machine Learning Visualization Extension](toolshed.g2.bx.psu.edu/repos/bgruening/ml_visualization_ex/ml_visualization_ex/1.0.10.0) %}
> - *"Select a plotting type"*: `Confusion matrix for classes`
> - *"Select dataset containing the true labels"*": `y_test`
> - *"Choose how to select data by column:"*: `All columns`
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN.ga b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN.ga
deleted file mode 100644
index 76b51f2c3ab263..00000000000000
--- a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN.ga
+++ /dev/null
@@ -1,466 +0,0 @@
-{
- "a_galaxy_workflow": "true",
- "annotation": "Introduction to RNNs",
- "format-version": "0.1",
- "name": "Intro_To_RNN",
- "steps": {
- "0": {
- "annotation": "",
- "content_id": null,
- "errors": null,
- "id": 0,
- "input_connections": {},
- "inputs": [
- {
- "description": "",
- "name": "X_test"
- }
- ],
- "label": "X_test",
- "name": "Input dataset",
- "outputs": [],
- "position": {
- "bottom": 342.6988639831543,
- "height": 61.73295211791992,
- "left": 680.9801025390625,
- "right": 880.9801025390625,
- "top": 280.9659118652344,
- "width": 200,
- "x": 680.9801025390625,
- "y": 280.9659118652344
- },
- "tool_id": null,
- "tool_state": "{\"optional\": false, \"tag\": null}",
- "tool_version": null,
- "type": "data_input",
- "uuid": "a5e70504-f58c-4e47-898e-e19862e263c8",
- "workflow_outputs": []
- },
- "1": {
- "annotation": "",
- "content_id": null,
- "errors": null,
- "id": 1,
- "input_connections": {},
- "inputs": [
- {
- "description": "",
- "name": "X_train"
- }
- ],
- "label": "X_train",
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+ "input_connections": {
+ "mode_selection|infile_json": {
+ "id": 4,
+ "output_name": "outfile"
+ }
+ },
+ "inputs": [],
+ "label": null,
+ "name": "Create deep learning model",
+ "outputs": [
+ {
+ "name": "outfile",
+ "type": "h5mlm"
+ }
+ ],
+ "position": {
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+ "top": 130
+ },
+ "post_job_actions": {},
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+ "changeset_revision": "66d7efc06000",
+ "name": "keras_model_builder",
+ "owner": "bgruening",
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+ "type": "tool",
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+ "output_name": "output"
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+ "input_options|infile2": {
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+ "output_name": "output"
+ }
+ },
+ "inputs": [],
+ "label": null,
+ "name": "Deep learning training and evaluation",
+ "outputs": [
+ {
+ "name": "outfile_result",
+ "type": "tabular"
+ },
+ {
+ "name": "outfile_object",
+ "type": "h5mlm"
+ }
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+ "top": 10
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+ "post_job_actions": {},
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/keras_train_and_eval/keras_train_and_eval/1.0.10.0",
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+ "changeset_revision": "818f9b69d8a0",
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+ "type": "tool",
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+ "input_options|infile1": {
+ "id": 0,
+ "output_name": "output"
+ }
+ },
+ "inputs": [],
+ "label": null,
+ "name": "Model Prediction",
+ "outputs": [
+ {
+ "name": "outfile_predict",
+ "type": "tabular"
+ }
+ ],
+ "position": {
+ "left": 670,
+ "top": 10
+ },
+ "post_job_actions": {},
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/model_prediction/model_prediction/1.0.10.0",
+ "tool_shed_repository": {
+ "changeset_revision": "9991c4ddde14",
+ "name": "model_prediction",
+ "owner": "bgruening",
+ "tool_shed": "toolshed.g2.bx.psu.edu"
+ },
+ "tool_state": "{\"__input_ext\": \"input\", \"chromInfo\": \"/cvmfs/data.galaxyproject.org/managed/len/ucsc/?.len\", \"infile_estimator\": null, \"input_options\": {\"selected_input\": \"tabular\", \"__current_case__\": 0, \"infile1\": null, \"header1\": false, \"column_selector_options_1\": {\"selected_column_selector_option\": \"all_columns\", \"__current_case__\": 4}}, \"method\": \"predict\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
+ "type": "tool",
+ "uuid": "84e00c86-0370-4232-b20d-1d54f8c00d6e",
+ "when": null,
+ "workflow_outputs": []
+ },
+ "9": {
+ "annotation": "",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/ml_visualization_ex/ml_visualization_ex/1.0.10.0",
+ "errors": null,
+ "id": 9,
+ "input_connections": {
+ "plotting_selection|infile_predicted": {
+ "id": 8,
+ "output_name": "outfile_predict"
+ },
+ "plotting_selection|infile_true": {
+ "id": 2,
+ "output_name": "output"
+ }
+ },
+ "inputs": [],
+ "label": null,
+ "name": "Machine Learning Visualization Extension",
+ "outputs": [
+ {
+ "name": "output",
+ "type": "html"
+ }
+ ],
+ "position": {
+ "left": 890,
+ "top": 10
+ },
+ "post_job_actions": {},
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/ml_visualization_ex/ml_visualization_ex/1.0.10.0",
+ "tool_shed_repository": {
+ "changeset_revision": "1588f9076e32",
+ "name": "ml_visualization_ex",
+ "owner": "bgruening",
+ "tool_shed": "toolshed.g2.bx.psu.edu"
+ },
+ "tool_state": "{\"__input_ext\": \"input\", \"chromInfo\": \"/cvmfs/data.galaxyproject.org/managed/len/ucsc/?.len\", \"plotting_selection\": {\"plot_type\": \"classification_confusion_matrix\", \"__current_case__\": 6, \"infile_true\": null, \"header_true\": false, \"column_selector_options_true\": {\"selected_column_selector_option\": \"all_columns\", \"__current_case__\": 4}, \"infile_predicted\": null, \"header_predicted\": true, \"title\": \"Confusion matrix between true and predicted labels\", \"plot_format\": \"png\", \"plot_color\": \"Greens\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": null,
+ "type": "tool",
+ "uuid": "46cc48a1-b1c9-49fe-9c3c-5996ed4cc592",
+ "when": null,
+ "workflow_outputs": []
+ }
+ },
+ "tags": [],
+ "uuid": "c995f5c8-de9c-4bc5-9a15-1060eb569d40",
+ "version": 1
+}
\ No newline at end of file
From 460ff689bfc719ea57ca1ec4ce4cd75efab68415 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Fri, 13 Oct 2023 17:26:12 -0400
Subject: [PATCH 21/31] Updated tutorial text
---
topics/statistics/tutorials/FNN/tutorial.md | 3 +--
topics/statistics/tutorials/RNN/tutorial.md | 3 +--
2 files changed, 2 insertions(+), 4 deletions(-)
diff --git a/topics/statistics/tutorials/FNN/tutorial.md b/topics/statistics/tutorials/FNN/tutorial.md
index 22c0e9a6aace4c..2237d9d36fd8cf 100644
--- a/topics/statistics/tutorials/FNN/tutorial.md
+++ b/topics/statistics/tutorials/FNN/tutorial.md
@@ -406,8 +406,7 @@ batch_size decides the size of this subset (which we set to 50). The model build
>
{: .hands_on}
-The training step generates 2 datasets. 1) accuracy of the trained model, 2) the trained model, downloadable as a zip file, and 3) the trained
-model weights, downloadable as an hdf5 file. These files are needed for prediction in the next step.
+The training step generates 2 datasets. 1) accuracy of the trained model, 2) the trained model, in h5mlm format. These files are needed for prediction in the next step.
## Model Prediction
diff --git a/topics/statistics/tutorials/RNN/tutorial.md b/topics/statistics/tutorials/RNN/tutorial.md
index 3fe444ffde29a2..30f9720f450c78 100644
--- a/topics/statistics/tutorials/RNN/tutorial.md
+++ b/topics/statistics/tutorials/RNN/tutorial.md
@@ -326,8 +326,7 @@ The model builder can be downloaded as a zip file.
>
{: .hands_on}
-The training step generates 3 datasets. 1) accuracy of the trained model, 2) the trained model, downloadable as a zip file, and 3) the trained
-model weights, downloadable as an hdf5 file. These files are needed for prediction in the next step.
+The training step generates 2 datasets. 1) accuracy of the trained model, 2) the trained model, in h5mlm format. These files are needed for prediction in the next step.
### **Model Prediction**
From 39ffc53dd513fdf5f3f2d051dd13970a49026c71 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 15:07:56 -0400
Subject: [PATCH 22/31] Added tests
---
.../workflows/Intro_To_FNN_v1.0.10_tests.yml | 19 +++++++++++++++++++
.../workflows/Intro_To_RNN_v1.0.10_tests.yml | 19 +++++++++++++++++++
2 files changed, 38 insertions(+)
create mode 100644 topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml
create mode 100644 topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml
new file mode 100644
index 00000000000000..2f7c81e11d3396
--- /dev/null
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml
@@ -0,0 +1,19 @@
+- doc: Test outline for Intro_To_FNN_v1.0.10.0
+ job:
+ X_test:
+ class: File
+ path: https://zenodo.org/records/4660497/files/X_test.tsv
+ filetype: tabular
+ X_train:
+ class: File
+ path: https://zenodo.org/records/4660497/files/X_train.tsv
+ filetype: tabular
+ y_test:
+ class: File
+ path: https://zenodo.org/records/4660497/files/y_test.tsv
+ filetype: tabular
+ y_train:
+ class: File
+ path: https://zenodo.org/records/4660497/files/y_train.tsv
+ filetype: tabular
+ outputs: {}
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml
new file mode 100644
index 00000000000000..697ad78f37ad8d
--- /dev/null
+++ b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml
@@ -0,0 +1,19 @@
+- doc: Test outline for Intro_To_RNN_v1.0.10.0
+ job:
+ X_test:
+ class: File
+ path: https://zenodo.org/records/4477881/files/X_test.tsv
+ filetype: tabular
+ X_train:
+ class: File
+ path: https://zenodo.org/records/4477881/files/X_train.tsv
+ filetype: tabular
+ y_test:
+ class: File
+ path: https://zenodo.org/records/4477881/files/y_test.tsv
+ filetype: tabular
+ y_train:
+ class: File
+ path: https://zenodo.org/records/4477881/files/y_train.tsv
+ filetype: tabular
+ outputs: {}
From 690768437c53565325208e4a65d7205c1a0b62ba Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 15:11:25 -0400
Subject: [PATCH 23/31] Updated versions in .ga file
---
.../tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga | 4 ++--
.../tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga | 4 ++--
2 files changed, 4 insertions(+), 4 deletions(-)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
index 1e34c50a9bbb34..015635003aaaf1 100644
--- a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
@@ -2,7 +2,7 @@
"a_galaxy_workflow": "true",
"annotation": "",
"format-version": "0.1",
- "name": "Intro_To_FNN_0.10.0",
+ "name": "Intro_To_FNN_v1.0.10.0",
"steps": {
"0": {
"annotation": "",
@@ -338,4 +338,4 @@
],
"uuid": "bd1e9e38-997b-41e0-9556-ccf13490fa08",
"version": 1
-}
\ No newline at end of file
+}
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
index 8a76d2481efe9b..a592704d8312c7 100644
--- a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
@@ -2,7 +2,7 @@
"a_galaxy_workflow": "true",
"annotation": "",
"format-version": "0.1",
- "name": "Intro_To_RNN_v0.10.0",
+ "name": "Intro_To_RNN_v1.0.10.0",
"steps": {
"0": {
"annotation": "",
@@ -365,4 +365,4 @@
"tags": [],
"uuid": "c995f5c8-de9c-4bc5-9a15-1060eb569d40",
"version": 1
-}
\ No newline at end of file
+}
From ef0a31135b8fd03d92b55b58f775a1099d96c494 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 16:14:43 -0400
Subject: [PATCH 24/31] Fixed some lint issues
---
.../tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga | 2 ++
topics/statistics/tutorials/RNN/tutorial.md | 10 +++++-----
.../tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga | 2 ++
3 files changed, 9 insertions(+), 5 deletions(-)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
index 015635003aaaf1..8d3b4f68a7adbb 100644
--- a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
@@ -1,7 +1,9 @@
{
"a_galaxy_workflow": "true",
"annotation": "",
+ "creator": [{"class": "Person", "name": "Kamali, Kaivan"}],
"format-version": "0.1",
+ "license": "CC-BY-4.0",
"name": "Intro_To_FNN_v1.0.10.0",
"steps": {
"0": {
diff --git a/topics/statistics/tutorials/RNN/tutorial.md b/topics/statistics/tutorials/RNN/tutorial.md
index 30f9720f450c78..796ddc94d63384 100644
--- a/topics/statistics/tutorials/RNN/tutorial.md
+++ b/topics/statistics/tutorials/RNN/tutorial.md
@@ -255,7 +255,7 @@ In the section, we define a RNN and train it using IMDB movie reviews training d
words in a review we can predict whether the review was positive or negative. We then evaluate the trained RNN on the test dataset
and plot the confusion matrix.
-### **Create a deep learning model architecture**
+## Create a deep learning model architecture
> Model config
>
@@ -284,7 +284,7 @@ an embedding layer, that transforms each review words into a 32 dimensional vect
*sigmoid* activation function, that generates an output between 0 and 1. Any output greater than 0.5 is considered a predicted positive review,
and anything less than 0.5 a negative one. The model config can be downloaded as a JSON file.
-### **Create a deep learning model**
+## Create a deep learning model
> Model builder (Optimizer, loss function, and fit parameters)
>
@@ -309,7 +309,7 @@ feed to the network, the training will be very slow (as we have 25000 training e
only a subset of the training examples to the network, after which we update the weights/biases. *batch_size* decides the size of this subset.
The model builder can be downloaded as a zip file.
-### **Deep learning training and evaluation**
+## Deep learning training and evaluation
> Training the model
>
@@ -328,7 +328,7 @@ The model builder can be downloaded as a zip file.
The training step generates 2 datasets. 1) accuracy of the trained model, 2) the trained model, in h5mlm format. These files are needed for prediction in the next step.
-### **Model Prediction**
+## Model Prediction
> Testing the model
>
@@ -346,7 +346,7 @@ The training step generates 2 datasets. 1) accuracy of the trained model, 2) the
The prediction step generates 1 dataset. It's a file that has predictions (1 or 0 for positive or negative movie reviews) for every review in
the test dataset.
-### **Machine Learning Visualization Extension**
+## Machine Learning Visualization Extension
> Creating the confusion matrix
>
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
index a592704d8312c7..7b74e393ddb98b 100644
--- a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
@@ -1,7 +1,9 @@
{
"a_galaxy_workflow": "true",
"annotation": "",
+ "creator": [{"class": "Person", "name": "Kamali, Kaivan"}],
"format-version": "0.1",
+ "license": "CC-BY-4.0",
"name": "Intro_To_RNN_v1.0.10.0",
"steps": {
"0": {
From 26c932f53cd779b422ff9319cc0e539ea28127b5 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 16:30:47 -0400
Subject: [PATCH 25/31] Added ORCHID ID to workflows
---
.../tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga | 2 +-
.../tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
index 8d3b4f68a7adbb..252b754caa7f6a 100644
--- a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
@@ -1,7 +1,7 @@
{
"a_galaxy_workflow": "true",
"annotation": "",
- "creator": [{"class": "Person", "name": "Kamali, Kaivan"}],
+ "creator": [{"class": "Person", "identifier":"0000-0001-6585-3619", "name": "Kaivan Kamali"}],
"format-version": "0.1",
"license": "CC-BY-4.0",
"name": "Intro_To_FNN_v1.0.10.0",
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
index 7b74e393ddb98b..5397869d02fc9f 100644
--- a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
@@ -1,7 +1,7 @@
{
"a_galaxy_workflow": "true",
"annotation": "",
- "creator": [{"class": "Person", "name": "Kamali, Kaivan"}],
+ "creator": [{"class": "Person", "identifier":"0000-0001-6585-3619", "name": "Kaivan Kamali"}],
"format-version": "0.1",
"license": "CC-BY-4.0",
"name": "Intro_To_RNN_v1.0.10.0",
From e702c92a5c4aa7ff36a714f4926c8babb4130252 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 17:19:39 -0400
Subject: [PATCH 26/31] Added tests
---
.../tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml | 6 +++++-
.../tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml | 6 +++++-
2 files changed, 10 insertions(+), 2 deletions(-)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml
index 2f7c81e11d3396..f52f6fcd5c3baa 100644
--- a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml
@@ -16,4 +16,8 @@
class: File
path: https://zenodo.org/records/4660497/files/y_train.tsv
filetype: tabular
- outputs: {}
+ outputs:
+ output_actual_vs_pred:
+ asserts:
+ has_text:
+ text: 'True vs predicted values'
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml
index 697ad78f37ad8d..f3c31fa06b59dd 100644
--- a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml
+++ b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml
@@ -16,4 +16,8 @@
class: File
path: https://zenodo.org/records/4477881/files/y_train.tsv
filetype: tabular
- outputs: {}
+ outputs:
+ output:
+ asserts:
+ has_text:
+ text: 'PNG'
From 6ee57369e0e7b6c93b2f3963ba0cd80251db9dec Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 17:29:00 -0400
Subject: [PATCH 27/31] Renamed test yml files
---
..._To_FNN_v1.0.10_tests.yml => Intro_To_FNN_v1.0.10.0_tests.yml} | 0
..._To_RNN_v1.0.10_tests.yml => Intro_To_RNN_v1.0.10.0_tests.yml} | 0
2 files changed, 0 insertions(+), 0 deletions(-)
rename topics/statistics/tutorials/FNN/workflows/{Intro_To_FNN_v1.0.10_tests.yml => Intro_To_FNN_v1.0.10.0_tests.yml} (100%)
rename topics/statistics/tutorials/RNN/workflows/{Intro_To_RNN_v1.0.10_tests.yml => Intro_To_RNN_v1.0.10.0_tests.yml} (100%)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0_tests.yml
similarity index 100%
rename from topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10_tests.yml
rename to topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0_tests.yml
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0_tests.yml
similarity index 100%
rename from topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10_tests.yml
rename to topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0_tests.yml
From d4055fe6e15e0ae6db4b17807957f5fa9d48c8bd Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 17:33:40 -0400
Subject: [PATCH 28/31] Renamed test yml files
---
...o_FNN_v1.0.10.0_tests.yml => Intro_To_FNN_v1.0.10.0-tests.yml} | 0
...o_RNN_v1.0.10.0_tests.yml => Intro_To_RNN_v1.0.10.0-tests.yml} | 0
2 files changed, 0 insertions(+), 0 deletions(-)
rename topics/statistics/tutorials/FNN/workflows/{Intro_To_FNN_v1.0.10.0_tests.yml => Intro_To_FNN_v1.0.10.0-tests.yml} (100%)
rename topics/statistics/tutorials/RNN/workflows/{Intro_To_RNN_v1.0.10.0_tests.yml => Intro_To_RNN_v1.0.10.0-tests.yml} (100%)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0_tests.yml b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0-tests.yml
similarity index 100%
rename from topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0_tests.yml
rename to topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0-tests.yml
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0_tests.yml b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0-tests.yml
similarity index 100%
rename from topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0_tests.yml
rename to topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0-tests.yml
From 72508012689459bf074ee58d075b7e92d91044f0 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 17:41:32 -0400
Subject: [PATCH 29/31] Got rid of . in workflow name
---
...FNN_v1.0.10.0-tests.yml => Intro_To_FNN_v1_0_10_0-tests.yml} | 2 +-
.../{Intro_To_FNN_v1.0.10.0.ga => Intro_To_FNN_v1_0_10_0.ga} | 2 +-
...RNN_v1.0.10.0-tests.yml => Intro_To_RNN_v1_0_10_0-tests.yml} | 2 +-
.../{Intro_To_RNN_v1.0.10.0.ga => Intro_To_RNN_v1_0_10_0.ga} | 2 +-
4 files changed, 4 insertions(+), 4 deletions(-)
rename topics/statistics/tutorials/FNN/workflows/{Intro_To_FNN_v1.0.10.0-tests.yml => Intro_To_FNN_v1_0_10_0-tests.yml} (92%)
rename topics/statistics/tutorials/FNN/workflows/{Intro_To_FNN_v1.0.10.0.ga => Intro_To_FNN_v1_0_10_0.ga} (99%)
rename topics/statistics/tutorials/RNN/workflows/{Intro_To_RNN_v1.0.10.0-tests.yml => Intro_To_RNN_v1_0_10_0-tests.yml} (92%)
rename topics/statistics/tutorials/RNN/workflows/{Intro_To_RNN_v1.0.10.0.ga => Intro_To_RNN_v1_0_10_0.ga} (99%)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0-tests.yml b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0-tests.yml
similarity index 92%
rename from topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0-tests.yml
rename to topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0-tests.yml
index f52f6fcd5c3baa..3bea4dc4366658 100644
--- a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0-tests.yml
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0-tests.yml
@@ -1,4 +1,4 @@
-- doc: Test outline for Intro_To_FNN_v1.0.10.0
+- doc: Test outline for Intro_To_FNN_v1_0_10_0
job:
X_test:
class: File
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0.ga
similarity index 99%
rename from topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
rename to topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0.ga
index 252b754caa7f6a..1be121c4c57563 100644
--- a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0.ga
@@ -4,7 +4,7 @@
"creator": [{"class": "Person", "identifier":"0000-0001-6585-3619", "name": "Kaivan Kamali"}],
"format-version": "0.1",
"license": "CC-BY-4.0",
- "name": "Intro_To_FNN_v1.0.10.0",
+ "name": "Intro_To_FNN_v1_0_10_0",
"steps": {
"0": {
"annotation": "",
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0-tests.yml b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0-tests.yml
similarity index 92%
rename from topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0-tests.yml
rename to topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0-tests.yml
index f3c31fa06b59dd..4144cab4a2de94 100644
--- a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0-tests.yml
+++ b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0-tests.yml
@@ -1,4 +1,4 @@
-- doc: Test outline for Intro_To_RNN_v1.0.10.0
+- doc: Test outline for Intro_To_RNN_v1_0_10_0
job:
X_test:
class: File
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0.ga
similarity index 99%
rename from topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
rename to topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0.ga
index 5397869d02fc9f..3d7ecca77e7af4 100644
--- a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1.0.10.0.ga
+++ b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0.ga
@@ -4,7 +4,7 @@
"creator": [{"class": "Person", "identifier":"0000-0001-6585-3619", "name": "Kaivan Kamali"}],
"format-version": "0.1",
"license": "CC-BY-4.0",
- "name": "Intro_To_RNN_v1.0.10.0",
+ "name": "Intro_To_RNN_v1_0_10_0",
"steps": {
"0": {
"annotation": "",
From f33b7dba42e8fba11deb641d7e5a595dfacb0152 Mon Sep 17 00:00:00 2001
From: Kaivan Kamali
Date: Mon, 16 Oct 2023 17:47:18 -0400
Subject: [PATCH 30/31] Renamed the .yml files
---
...To_FNN_v1_0_10_0-tests.yml => Intro_To_FNN_v1_0_10_0-test.yml} | 0
...To_RNN_v1_0_10_0-tests.yml => Intro_To_RNN_v1_0_10_0-test.yml} | 0
2 files changed, 0 insertions(+), 0 deletions(-)
rename topics/statistics/tutorials/FNN/workflows/{Intro_To_FNN_v1_0_10_0-tests.yml => Intro_To_FNN_v1_0_10_0-test.yml} (100%)
rename topics/statistics/tutorials/RNN/workflows/{Intro_To_RNN_v1_0_10_0-tests.yml => Intro_To_RNN_v1_0_10_0-test.yml} (100%)
diff --git a/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0-tests.yml b/topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0-test.yml
similarity index 100%
rename from topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0-tests.yml
rename to topics/statistics/tutorials/FNN/workflows/Intro_To_FNN_v1_0_10_0-test.yml
diff --git a/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0-tests.yml b/topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0-test.yml
similarity index 100%
rename from topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0-tests.yml
rename to topics/statistics/tutorials/RNN/workflows/Intro_To_RNN_v1_0_10_0-test.yml
From 25092919206bef9737507b3d6a453437010d120d Mon Sep 17 00:00:00 2001
From: Maria Doyle
Date: Wed, 18 Oct 2023 09:56:55 +0100
Subject: [PATCH 31/31] Fix zenodo links
---
.../tutorials/crispr-screen/data-library.yaml | 20 +++++++++----------
.../tutorials/crispr-screen/tutorial.md | 20 +++++++++----------
2 files changed, 20 insertions(+), 20 deletions(-)
diff --git a/topics/genome-annotation/tutorials/crispr-screen/data-library.yaml b/topics/genome-annotation/tutorials/crispr-screen/data-library.yaml
index bd605fae98d306..22d3d3dc414b9a 100644
--- a/topics/genome-annotation/tutorials/crispr-screen/data-library.yaml
+++ b/topics/genome-annotation/tutorials/crispr-screen/data-library.yaml
@@ -13,43 +13,43 @@ items:
- name: 'DOI: 10.5281/zenodo.5750854'
description: latest
items:
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/adapters_list.tsv
+ - url: https://zenodo.org/records/5750854/files/adapter_list.tsv
src: url
ext: tsv
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/brunello.tsv
+ - url: https://zenodo.org/records/5750854/files/brunello.tsv
src: url
ext: tsv
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/h.all.v7.4.symbols.gmt
+ - url: https://zenodo.org/records/5750854/files/h.all.v7.4.symbols.gmt
src: url
ext: tsv
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_count_summary.tsv
+ - url: https://zenodo.org/records/5750854/files/kenji_mageck_count_summary.tsv
src: url
ext: tsv
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_count_report.pdf
+ - url: https://zenodo.org/records/5750854/files/kenji_mageck_count_report.pdf
src: url
ext: tsv
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_sgrna_counts.tsv
+ - url: https://zenodo.org/records/5750854/files/kenji_mageck_sgrna_counts.tsv
src: url
ext: tsv
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_mle_design_matrix.tsv
+ - url: https://zenodo.org/records/5750854/files/kenji_mageck_mle_design_matrix.tsv
src: url
ext: tsv
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/T0-Control.fastq.gz
+ - url: https://zenodo.org/records/5750854/files/T0-Control.fastq.gz
src: url
ext: gz
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/T8-APR-246.fastq.gz
+ - url: https://zenodo.org/records/5750854/files/T8-APR-246.fastq.gz
src: url
ext: gz
info: https://zenodo.org/record/5750854
- - url: https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/T8-Vehicle.fastq.gz
+ - url: https://zenodo.org/records/5750854/files/T8-Vehicle.fastq.gz
src: url
ext: gz
info: https://zenodo.org/record/5750854
diff --git a/topics/genome-annotation/tutorials/crispr-screen/tutorial.md b/topics/genome-annotation/tutorials/crispr-screen/tutorial.md
index 021f3c46473968..fa026603b3e6d7 100644
--- a/topics/genome-annotation/tutorials/crispr-screen/tutorial.md
+++ b/topics/genome-annotation/tutorials/crispr-screen/tutorial.md
@@ -78,9 +78,9 @@ Here we will demonstrate analysing {CRISPR} screen using data from {% cite Fujih
> - Copy the following tabular data, paste it into the textbox and press Build
>
> ```
-> T0-Control https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/T0-Control.fastq.gz
-> T8-APR-246 https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/T8-APR-246.fastq.gz
-> T8-Vehicle https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/T8-Vehicle.fastq.gz
+> T0-Control https://zenodo.org/records/5750854/files/T0-Control.fastq.gz
+> T8-APR-246 https://zenodo.org/records/5750854/files/T8-APR-246.fastq.gz
+> T8-Vehicle https://zenodo.org/records/5750854/files/T8-Vehicle.fastq.gz
> ```
>
> 
@@ -118,7 +118,7 @@ With CRISPR screens we expect adapter sequence to be present, surrounding the gu
>
> 1. Import the adapters file from [Zenodo]({{ page.zenodo_link }}) or the Shared Data library (if available):
> ```
-> https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/adapter_list.tsv
+> https://zenodo.org/records/5750854/files/adapter_list.tsv
> ```
> {% snippet faqs/galaxy/datasets_import_via_link.md %}
>
@@ -246,7 +246,7 @@ To count how many guides we have for each gene, we need a library file that tell
> Count guides per gene
> 1. Import the sgRNA library file
> ```
-> https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/brunello.tsv
+> https://zenodo.org/records/5750854/files/brunello.tsv
> ```
>
> 2. {% tool [MAGeCK count](toolshed.g2.bx.psu.edu/repos/iuc/mageck_count/mageck_count/0.5.9.2.4) %} with the following parameters:
@@ -259,9 +259,9 @@ To count how many guides we have for each gene, we need a library file that tell
>
> 3. We have been using 1% of reads from the samples. Import the MAGeCK count files (sgRNA counts, counts summary and plots pdf) for the full dataset so you can see what results for a real dataset looks like.
> ```
-> https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_sgrna_counts.tsv
-> https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_count_summary.tsv
-> https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_count_report.pdf
+> https://zenodo.org/records/5750854/files/kenji_mageck_sgrna_counts.tsv
+> https://zenodo.org/records/5750854/files/kenji_mageck_count_summary.tsv
+> https://zenodo.org/records/5750854/files/kenji_mageck_count_report.pdf
> ```
>
{: .hands_on}
@@ -569,7 +569,7 @@ We can perform pathway analysis on the results to identify pathways that are cha
>
> 1. Import the Hallmark pathways file [Zenodo]({{ page.zenodo_link }}) or the Shared Data library (if available). Set the Type to tabular:
> ```
-> https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/h.all.v7.4.symbols.gmt
+> https://zenodo.org/records/5750854/files/h.all.v7.4.symbols.gmt
> ```
> {% snippet faqs/galaxy/datasets_change_datatype.md %}
>
@@ -629,7 +629,7 @@ Examples of more complicated design matrices, for e.g. time series experiments,
> Test for enrichment with MLE
> 1. Import the design matrix file from [Zenodo]({{ page.zenodo_link }}) or the Shared Data library (if available):
> ```
-> https://zenodo.org/api/files/6599878c-f569-41bf-a37a-2c6f3d2e67f9/kenji_mageck_mle_design_matrix.tsv
+> https://zenodo.org/records/5750854/files/kenji_mageck_mle_design_matrix.tsv
> ```
>
> 2. {% tool [MAGeCKs mle](toolshed.g2.bx.psu.edu/repos/iuc/mageck_mle/mageck_mle/0.5.9.2.1) %} with the following parameters: