From 48cd410c171153238b5831a117d6bbb2153cd697 Mon Sep 17 00:00:00 2001 From: Lucille Delisle Date: Thu, 19 Oct 2023 17:41:44 +0200 Subject: [PATCH 1/7] fix snippet copy dataset --- faqs/galaxy/histories_copy_dataset.md | 24 +++++++++++++++--------- 1 file changed, 15 insertions(+), 9 deletions(-) diff --git a/faqs/galaxy/histories_copy_dataset.md b/faqs/galaxy/histories_copy_dataset.md index 2529b71c70ac20..0134363314c36e 100644 --- a/faqs/galaxy/histories_copy_dataset.md +++ b/faqs/galaxy/histories_copy_dataset.md @@ -4,26 +4,32 @@ description: Sometimes you may want to use a dataset in multiple histories. You area: histories box_type: tip layout: faq -contributors: [lecorguille,shiltemann,hexylena,bebatut] +contributors: [lecorguille,shiltemann,hexylena,bebatut,lldelisle] --- There 3 ways to copy datasets between histories + 1. From the original history - 1. Click on the {% icon galaxy-gear %} icon (**History options**) on the top of the history panel - 2. Click on **Copy Dataset** + 1. Click on the {% icon galaxy-gear %} icon which is on the top of the list of datasets in the history panel + 2. Click on **Copy Datasets** 3. Select the desired files {% if include.history_name %} - 4. "New history name:" `{{ include.history_name }}` + 4. "New history named:" `{{ include.history_name }}` {% else %} 4. Give a relevant name to the "New history" {% endif %} + 5. Validate by 'Copy History Items' 5. Click on the new history name in the green box that have just appear to switch to this history -2. From the {% icon galaxy-columns %} **View all histories** +2. Using the {% icon galaxy-columns %} **Show Histories Side-by-Side** - 1. Click on {% icon galaxy-columns %} **View all histories** on the top right - 2. Switch to the history in which the dataset should be copied + 1. Click on the {% icon galaxy-dropdown %} dropdown arrow top right of the history panel (**History options**) + 2. Click on {% icon galaxy-columns %} **Show Histories Side-by-Side** + 3. If your target history is not present + 1. Click on 'Select histories' + 2. Click on your target history + 3. Validate by 'Change Selected' 3. Drag the dataset to copy from its original history 4. Drop it in the target history @@ -32,5 +38,5 @@ There 3 ways to copy datasets between histories 1. Click on **User** in the top bar 2. Click on **Datasets** 3. Search for the dataset to copy - 4. Click on it - 5. Click on **Copy to History** \ No newline at end of file + 4. Click on its name + 5. Click on **Copy to current History** From b6dc8a426361055734e9da5daa3284ab24e50662 Mon Sep 17 00:00:00 2001 From: Hans-Rudolf Hotz Date: Fri, 20 Oct 2023 07:39:33 +0200 Subject: [PATCH 2/7] samll fixes to Reference-based RNA-Seq data analysis --- topics/transcriptomics/tutorials/ref-based/tutorial.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/topics/transcriptomics/tutorials/ref-based/tutorial.md b/topics/transcriptomics/tutorials/ref-based/tutorial.md index 19a2dc80bfc052..28f57854f68b80 100644 --- a/topics/transcriptomics/tutorials/ref-based/tutorial.md +++ b/topics/transcriptomics/tutorials/ref-based/tutorial.md @@ -1729,7 +1729,7 @@ Now we would like to extract the most differentially expressed genes due to the > > We will now select only the genes with a fold change (FC) > 2 or FC < 0.5. Note that the DESeq2 output file contains $$log_{2} FC$$, rather than FC itself, so we filter for $$abs(log_{2} FC) > 1$$ (which implies FC > 2 or FC < 0.5). > -> 3. {% tool [Filter](Filter1) %} to extract genes with an $$abs(log_{2} FC) > 1$$: +> 3. {% tool [Filter data on any column using simple expressions](Filter1) %} to extract genes with an $$abs(log_{2} FC) > 1$$: > - {% icon param-file %} *"Filter"*: `Genes with significant adj p-value` > - *"With following condition"*: `abs(c3)>1` > - *"Number of header lines to skip"*: `1` @@ -1743,7 +1743,7 @@ Now we would like to extract the most differentially expressed genes due to the > > > > > > > > -> > > 1. 114, or 11.79% of the significantly differentially expressed genes. +> > > 1. We get 113 (114 lines including a header) genes, or 11.79% of the significantly differentially expressed genes. > > > 2. The *Pasilla* gene can be found with a quick Search (or even using {% tool [Filter data on any column using simple expressions](Filter1) %} ) > > {: .solution} > {: .question} @@ -1822,7 +1822,7 @@ You should obtain something similar to: > > > > > -> > 1. The X-axis shows the 7 samples, together with a dendrogram representing the similarity between their levels of gene expression. The Y-axis shows the 130 differentially expressed genes, likewise with a dendrogram representing the similarity between the levels of gene expression. +> > 1. The X-axis shows the 7 samples, together with a dendrogram representing the similarity between their levels of gene expression. The Y-axis shows the 113 differentially expressed genes, likewise with a dendrogram representing the similarity between the levels of gene expression. > > 2. The samples are clustering by treatment. > > 3. The scale changes and we only see few genes. > > 4. Because the normalized expression of the gene `FBgn0013688` in `GSM461180_treat_paired` is at `0`. @@ -2097,9 +2097,9 @@ For example, the pathway `dme00010` represents the glycolysis process (conversio > > > > > > 1. The file has 128 lines including an header, so 127 KEGG pathways have been identified. - > > 2. 2 KEGG pathways (2.34%) are over-represented, using **Filter** on c6 (adjusted p-value for over-represented KEGG pathways) + > > 2. 2 KEGG pathways (2.34%) are over-represented, using {% tool [Filter](Filter1) %} on c6 (adjusted p-value for over-represented KEGG pathways) > > 3. The 2 KEGG pathways over-represented are `01100` and `00010`. By searching on the [KEGG database](https://www.genome.jp/kegg/kegg2.html) for them, we can find more information about these pathways: `01100` corresponds to all metabolic pathways and `00010` to pathway for Glycolysis / Gluconeogenesis. - > > 4. No KEGG pathway is under-represented, using **Filter** on c7 (adjusted p-value for under-represented KEGG pathways) + > > 4. No KEGG pathway is under-represented, using {% tool [Filter](Filter1) %} on c7 (adjusted p-value for under-represented KEGG pathways) > {: .solution} {: .question} From 17641a7aff569f7d76c5f1c81402d365de9d0cb7 Mon Sep 17 00:00:00 2001 From: Hans-Rudolf Hotz Date: Fri, 20 Oct 2023 09:07:19 +0200 Subject: [PATCH 3/7] Update topics/transcriptomics/tutorials/ref-based/tutorial.md Co-authored-by: Lucille Delisle --- topics/transcriptomics/tutorials/ref-based/tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/topics/transcriptomics/tutorials/ref-based/tutorial.md b/topics/transcriptomics/tutorials/ref-based/tutorial.md index 28f57854f68b80..42a9e47bc5415b 100644 --- a/topics/transcriptomics/tutorials/ref-based/tutorial.md +++ b/topics/transcriptomics/tutorials/ref-based/tutorial.md @@ -1743,7 +1743,7 @@ Now we would like to extract the most differentially expressed genes due to the > > > > > > > > -> > > 1. We get 113 (114 lines including a header) genes, or 11.79% of the significantly differentially expressed genes. +> > > 1. We get 113 genes (114 lines including a header), or 11.79% of the significantly differentially expressed genes. > > > 2. The *Pasilla* gene can be found with a quick Search (or even using {% tool [Filter data on any column using simple expressions](Filter1) %} ) > > {: .solution} > {: .question} From 0d5bb3869193e96f5c3c87141dfc55cf18a6cd77 Mon Sep 17 00:00:00 2001 From: Hans-Rudolf Hotz Date: Fri, 20 Oct 2023 09:07:40 +0200 Subject: [PATCH 4/7] Update topics/transcriptomics/tutorials/ref-based/tutorial.md Co-authored-by: Lucille Delisle --- topics/transcriptomics/tutorials/ref-based/tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/topics/transcriptomics/tutorials/ref-based/tutorial.md b/topics/transcriptomics/tutorials/ref-based/tutorial.md index 42a9e47bc5415b..8e2dadf593cdc4 100644 --- a/topics/transcriptomics/tutorials/ref-based/tutorial.md +++ b/topics/transcriptomics/tutorials/ref-based/tutorial.md @@ -2097,7 +2097,7 @@ For example, the pathway `dme00010` represents the glycolysis process (conversio > > > > > > 1. The file has 128 lines including an header, so 127 KEGG pathways have been identified. - > > 2. 2 KEGG pathways (2.34%) are over-represented, using {% tool [Filter](Filter1) %} on c6 (adjusted p-value for over-represented KEGG pathways) + > > 2. 2 KEGG pathways (2.34%) are over-represented, using {% tool [Filter data on any column using simple expressions](Filter1) %} on c6 (adjusted p-value for over-represented KEGG pathways) > > 3. The 2 KEGG pathways over-represented are `01100` and `00010`. By searching on the [KEGG database](https://www.genome.jp/kegg/kegg2.html) for them, we can find more information about these pathways: `01100` corresponds to all metabolic pathways and `00010` to pathway for Glycolysis / Gluconeogenesis. > > 4. No KEGG pathway is under-represented, using {% tool [Filter](Filter1) %} on c7 (adjusted p-value for under-represented KEGG pathways) > {: .solution} From 97b078449cd5398930f1aa5dff60142f68157de2 Mon Sep 17 00:00:00 2001 From: Hans-Rudolf Hotz Date: Fri, 20 Oct 2023 09:07:52 +0200 Subject: [PATCH 5/7] Update topics/transcriptomics/tutorials/ref-based/tutorial.md Co-authored-by: Lucille Delisle --- topics/transcriptomics/tutorials/ref-based/tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/topics/transcriptomics/tutorials/ref-based/tutorial.md b/topics/transcriptomics/tutorials/ref-based/tutorial.md index 8e2dadf593cdc4..10a03b9609d4d9 100644 --- a/topics/transcriptomics/tutorials/ref-based/tutorial.md +++ b/topics/transcriptomics/tutorials/ref-based/tutorial.md @@ -2099,7 +2099,7 @@ For example, the pathway `dme00010` represents the glycolysis process (conversio > > 1. The file has 128 lines including an header, so 127 KEGG pathways have been identified. > > 2. 2 KEGG pathways (2.34%) are over-represented, using {% tool [Filter data on any column using simple expressions](Filter1) %} on c6 (adjusted p-value for over-represented KEGG pathways) > > 3. The 2 KEGG pathways over-represented are `01100` and `00010`. By searching on the [KEGG database](https://www.genome.jp/kegg/kegg2.html) for them, we can find more information about these pathways: `01100` corresponds to all metabolic pathways and `00010` to pathway for Glycolysis / Gluconeogenesis. - > > 4. No KEGG pathway is under-represented, using {% tool [Filter](Filter1) %} on c7 (adjusted p-value for under-represented KEGG pathways) + > > 4. No KEGG pathway is under-represented, using {% tool [Filter data on any column using simple expressions](Filter1) %} on c7 (adjusted p-value for under-represented KEGG pathways) > {: .solution} {: .question} From cc1ffd416bb4191f51a980b85483520744fbbede Mon Sep 17 00:00:00 2001 From: Hans-Rudolf Hotz Date: Fri, 20 Oct 2023 09:40:16 +0200 Subject: [PATCH 6/7] Update tutorial.md --- topics/transcriptomics/tutorials/ref-based/tutorial.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/topics/transcriptomics/tutorials/ref-based/tutorial.md b/topics/transcriptomics/tutorials/ref-based/tutorial.md index 10a03b9609d4d9..18e4e6286b801f 100644 --- a/topics/transcriptomics/tutorials/ref-based/tutorial.md +++ b/topics/transcriptomics/tutorials/ref-based/tutorial.md @@ -2029,7 +2029,7 @@ We have now the two required input files for goseq. > > > > 1. 60 GO terms (0.50%) are over-represented and 7 (0.07%) under-represented. > > - > > {% tool [Filter](Filter1) %} on c8 (adjusted p-value for over-represented GO terms) and c9 (adjusted p-value for under-represented GO terms) + > > {% tool [Filter data on any column using simple expressions](Filter1) %} on c8 (adjusted p-value for over-represented GO terms) and c9 (adjusted p-value for under-represented GO terms) > > > > 2. For over-represented, 50 BP, 5 CC and 5 MF and for under-represented, 5 BP, 2 CC and 0 MF > > @@ -2295,7 +2295,7 @@ Similarly to DESeq2, DEXSeq generates a table with: > > -> 1. {% tool [Filter](Filter1) %} to extract exons with a significant differential usage (adjusted *p*-value equal or below 0.05) between treated and untreated samples +> 1. {% tool [Filter data on any column using simple expressions](Filter1) %} to extract exons with a significant differential usage (adjusted *p*-value equal or below 0.05) between treated and untreated samples > > > > > From 3377d5c6f10ab4de9f148bd911edd67ac2e83eee Mon Sep 17 00:00:00 2001 From: Lucille Delisle Date: Fri, 20 Oct 2023 15:31:21 +0200 Subject: [PATCH 7/7] update workflow to have steps in the same order as in the tutorial --- .../workflows/qc-mapping-counting-test.yml | 6 +- .../workflows/qc-mapping-counting.ga | 3501 +++++++++++------ 2 files changed, 2354 insertions(+), 1153 deletions(-) diff --git a/topics/transcriptomics/tutorials/ref-based/workflows/qc-mapping-counting-test.yml b/topics/transcriptomics/tutorials/ref-based/workflows/qc-mapping-counting-test.yml index 716937ab0c0987..122ae40ba3dfb7 100644 --- a/topics/transcriptomics/tutorials/ref-based/workflows/qc-mapping-counting-test.yml +++ b/topics/transcriptomics/tutorials/ref-based/workflows/qc-mapping-counting-test.yml @@ -31,10 +31,8 @@ filetype: fastqsanger Drosophila_melanogaster.BDGP6.32.109_UCSC.gtf.gz: class: File - # Can be uncommented when https://github.com/galaxyproject/galaxy/pull/16014 is merged - # location: https://zenodo.org/record/6457007/files/Drosophila_melanogaster.BDGP6.32.109_UCSC.gtf.gz - # decompress: true - path: test-data/Drosophila_melanogaster.BDGP6.32.109_UCSC.gtf + location: https://zenodo.org/record/6457007/files/Drosophila_melanogaster.BDGP6.32.109_UCSC.gtf.gz + decompress: true filetype: gtf outputs: multiqc_cutadapt_html: diff --git 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