Merge pull request #4557 from EngyNasr/tagsAfflicationandcontribution

Adding MicroGalaxy tag to Microbiom training materials, so we can add then in the microgalaxy webserver
galaxyproject · Nov 28, 2023 · 5ec29c5 · 5ec29c5
2 parents eac2ce4 + 9b8b6ed
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diff --git a/topics/assembly/tutorials/ecoli_comparison/tutorial.md b/topics/assembly/tutorials/ecoli_comparison/tutorial.md
@@ -11,6 +11,7 @@ requirements:
       - unicycler-assembly
 tags:
   - prokaryote
+  - microgalaxy
 questions:
   - "I just assembled a genome. How does it compare with already sequenced genomes?"
   - "How do I find rearranged, inserted, or deleted regions?"

diff --git a/topics/assembly/tutorials/unicycler-assembly/tutorial.md b/topics/assembly/tutorials/unicycler-assembly/tutorial.md
@@ -6,6 +6,7 @@ zenodo_link: "https://doi.org/10.5281/zenodo.940733"
 level: Introductory
 tags:
   - prokaryote
+  - microgalaxy
 questions:
   - "I have short reads and long reads. How do I assemble a genome?"
 objectives:
@@ -268,7 +269,7 @@ Let's look at the entire assembly and its annotation in the genome browser. We c
 
 Visualization requires a local installation of IGV. If you have IGV installed - just start it. If you don't - read on.
 
-#### Starting IGV
+### Starting IGV
 
 Go to IGV [download page](http://software.broadinstitute.org/software/igv/download) and select one of the options. The one I would try first would be **Java Web Start**. Simply click the **Launch** button for 10 GB distribution.
 

diff --git a/topics/evolution/tutorials/mtb_phylogeny/tutorial.md b/topics/evolution/tutorials/mtb_phylogeny/tutorial.md
@@ -32,6 +32,7 @@ tags:
 - prokaryote
 - one-health
 - phylogenetics
+- microgalaxy
 ---
 
 

diff --git a/topics/evolution/tutorials/mtb_transmission/tutorial.md b/topics/evolution/tutorials/mtb_transmission/tutorial.md
@@ -36,6 +36,7 @@ contributions:
 tags:
 - prokaryote
 - one-health
+- microgalaxy
 ---
 
 

diff --git a/topics/genome-annotation/tutorials/annotation-with-prokka/tutorial.md b/topics/genome-annotation/tutorials/annotation-with-prokka/tutorial.md
@@ -5,6 +5,7 @@ title: "Genome annotation with Prokka"
 zenodo_link: "https://doi.org/10.5281/zenodo.1156405"
 tags:
   - prokaryote
+  - microgalaxy
 questions:
   - "How can we annotate a bacterial genome?"
   - "How can we visualize annotated genomic features?"
@@ -26,7 +27,7 @@ subtopic: prokaryote
 
 In this section we will use a software tool called Prokka to annotate a draft genome sequence. Prokka is a “wrapper”; it collects together several pieces of software (from various authors), and so avoids “re-inventing the wheel”.
 
-Prokka finds and annotates features (both protein coding regions and RNA genes, i.e. tRNA, rRNA) present on on a sequence. Note, Prokka uses a two-step process for the annotation of protein coding regions: first, protein coding regions on the genome are identified using [Prodigal](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2848648/); second, the *function* of the encoded protein is predicted by similarity to proteins in one of many protein or protein domain databases. Prokka is a software tool that can be used to annotate bacterial, archaeal and viral genomes quickly, generating standard output files in GenBank, EMBL and gff formats. More information about Prokka can be found [here](https://github.com/tseemann/prokka).
+Prokka finds and annotates features (both protein coding regions and RNA genes, i.e. tRNA, rRNA) present on on a sequence. Note, Prokka uses a two-step process for the annotation of protein coding regions: first, protein coding regions on the genome are identified using [Prodigal](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2848648/); second, the *function* of the encoded protein is predicted by similarity to proteins in one of many protein or protein domain databases. Prokka is a software tool that can be used to annotate bacterial, archaeal and viral genomes quickly, generating standard output files in GenBank, EMBL and gff formats. More information about Prokka can be found in [Pokka's github link](https://github.com/tseemann/prokka).
 
 > <agenda-title></agenda-title>
 >

diff --git a/topics/genome-annotation/tutorials/apollo/tutorial.md b/topics/genome-annotation/tutorials/apollo/tutorial.md
@@ -5,6 +5,7 @@ title: Refining Genome Annotations with Apollo (prokaryotes)
 zenodo_link: https://zenodo.org/record/4889110
 tags:
   - prokaryote
+  - microgalaxy
 questions:
   - How to visualize your genome after automated annotations have been performed?
   - How to manually annotate genome after automated annotations have been performed?

diff --git a/topics/genome-annotation/tutorials/gene-centric/tutorial.md b/topics/genome-annotation/tutorials/gene-centric/tutorial.md
@@ -20,6 +20,7 @@ tags:
 - cookbook
 - eukaryote
 - prokaryote
+- microgalaxy
 requirements:
   -
     type: "internal"
@@ -351,7 +352,7 @@ This is a URL pointing to one of the workflow outputs: `Mapping report` with the
 
 Running the notebook will generate two graphs explained in the next section.
 
-### Interpreting the graphs
+## Interpreting the graphs
 
 Analysis of sample data associated with this tutorial will produce the genome graph shown below. In this graph the Y-axis represents ORFs on positive (1, 2, 3 in red color) and negative (-1, -2, -3 in blue color) strands. The X-axis is genomic coordinates.  Boxes represent matches between amino acid sequences of exons and ORFs they are superimposed to. The color of boxes reflect the extent of amino acid identity. The color key is shown in the left upper corner of the plot. The image is interactive so you can zoom in and out.
 

diff --git a/topics/metagenomics/tutorials/beer-data-analysis/tutorial.md b/topics/metagenomics/tutorials/beer-data-analysis/tutorial.md
@@ -23,6 +23,7 @@ tags:
 - beer
 - citizen science
 - metagenomics
+- microgalaxy
 contributions:
     authorship:
     - plushz

diff --git a/topics/metagenomics/tutorials/general-tutorial/tutorial.md b/topics/metagenomics/tutorials/general-tutorial/tutorial.md
@@ -21,6 +21,8 @@ key_points:
 contributors:
   - shiltemann
   - bebatut
+tags:
+  - microgalaxy
 ---
 
 

diff --git a/topics/metagenomics/tutorials/metagenomics-assembly/tutorial.md b/topics/metagenomics/tutorials/metagenomics-assembly/tutorial.md
@@ -35,6 +35,7 @@ contributions:
 tags:
   - assembly
   - metagenomics
+  - microgalaxy
 ---
 
 

diff --git a/topics/metagenomics/tutorials/metatranscriptomics-short/tutorial.md b/topics/metagenomics/tutorials/metatranscriptomics-short/tutorial.md
@@ -15,6 +15,7 @@ objectives:
 level: Introductory
 tags:
 - metatranscriptomics
+- microgalaxy
 time_estimation: 3H
 key_points:
 - Metatranscriptomics data have the same QC profile that RNA-seq data
@@ -30,6 +31,7 @@ contributors:
 - pravs3683
 - shiltemann
 - paulzierep
+- EngyNasr
 ---
 
 

diff --git a/topics/metagenomics/tutorials/metatranscriptomics/tutorial.md b/topics/metagenomics/tutorials/metatranscriptomics/tutorial.md
@@ -15,6 +15,7 @@ objectives:
 level: Introductory
 tags:
 - metatranscriptomics
+- microgalaxy
 time_estimation: 5H
 key_points:
 - Metatranscriptomics data have the same QC profile that RNA-seq data
@@ -32,6 +33,7 @@ contributors:
 - pravs3683
 - shiltemann
 - paulzierep
+- EngyNasr
 ---
 
 {% include topics/metagenomics/tutorials/metatranscriptomics/content.md short=false %}
diff --git a/topics/metagenomics/tutorials/mothur-miseq-sop-short/tutorial.md b/topics/metagenomics/tutorials/mothur-miseq-sop-short/tutorial.md
@@ -19,6 +19,8 @@ contributors:
   - shiltemann
   - bebatut
   - tnabtaf
+tags:
+  - microgalaxy
 ---
 
 {% include topics/metagenomics/tutorials/mothur-miseq-sop/content.md short=true %}

diff --git a/topics/metagenomics/tutorials/mothur-miseq-sop/tutorial.md b/topics/metagenomics/tutorials/mothur-miseq-sop/tutorial.md
@@ -19,6 +19,8 @@ contributors:
   - shiltemann
   - bebatut
   - tnabtaf
+tags:
+  - microgalaxy
 ---
 
 {% include topics/metagenomics/tutorials/mothur-miseq-sop/content.md short=false %}
diff --git a/...agenomics/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md b/...agenomics/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md
@@ -3,6 +3,7 @@ layout: tutorial_hands_on
 
 title: "Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition"
 tags:
+    - microgalaxy
     - Nanopore data analysis
     - Pathogens detection
     - Phylogenetic tree

diff --git a/topics/proteomics/tutorials/metaproteomics/tutorial.md b/topics/proteomics/tutorials/metaproteomics/tutorial.md
@@ -22,7 +22,7 @@ contributors:
   - blankclemens
   - subinamehta
 subtopic: multi-omics
-tags: [microbiome]
+tags: [microgalaxy]
 ---
 
 In this metaproteomics tutorial we will identify expressed proteins from a complex bacterial community sample.

diff --git a/topics/proteomics/tutorials/metaquantome-data-creation/tutorial.md b/topics/proteomics/tutorials/metaquantome-data-creation/tutorial.md
@@ -31,7 +31,7 @@ follow_up_training:
             - metaproteomics
 
 subtopic: multi-omics
-tags: [microbiome]
+tags: [microgalaxy]
 ---
 
 

diff --git a/topics/proteomics/tutorials/metaquantome-function/tutorial.md b/topics/proteomics/tutorials/metaquantome-function/tutorial.md
@@ -38,7 +38,7 @@ requirements:
     tutorials:
       - metaquantome-data-creation
 subtopic: multi-omics
-tags: [microbiome]
+tags: [microgalaxy]
 ---
 
 
@@ -60,12 +60,12 @@ In this tutorial, we will learn specifically about the metaQuantome Function wor
 {: .agenda}
 
 
-# **Pretreatments**
+# Pretreatments
 
 The first step in this tutorial is to get the data from the Zenodo link provided and make sure that it is in the correct format.
 
 
-## *Get data*
+## Get data
 
 > <hands-on-title>Data upload</hands-on-title>
 >
@@ -93,7 +93,7 @@ The first step in this tutorial is to get the data from the Zenodo link provided
 >
 {: .hands_on}
 
-# **Download metaQuantome Databases**
+# Download metaQuantome Databases
 
 > <hands-on-title>Run metaQuantome databases</hands-on-title>
 >
@@ -134,7 +134,7 @@ The first step in this tutorial is to get the data from the Zenodo link provided
 >
 {: .question}
 
-# **Create metaQuantome sample file**
+# Create metaQuantome sample file
 
 The create samples file module is used to generate the samples file input file for the metaQuantome workflow. This input file is used to specify the column names used for each experimental group. These column names are referenced when handling the input data and performing statistical analysis.
 
@@ -157,10 +157,10 @@ The create samples file module is used to generate the samples file input file f
 {: .hands_on}
 
 
-# **Run metaQuantome**
+# Run metaQuantome
 
 
-## *metaQuantome: expand*
+## metaQuantome: expand
 
 The expand module is the first analysis step in the metaQuantome analysis workflow, and can be run to analyze differently expressed functions in the samples.
 In function mode, the following information is required apart from metaQuantome databases and samples file:
@@ -198,7 +198,7 @@ In function mode, the following information is required apart from metaQuantome
 {: .hands_on}
 
 
-##  *metaQuantome: filter*
+##  metaQuantome: filter
 
 The filter module is the second step in the metaQuantome workflow. The filter module filters the expanded terms to those that are representative of the data according to the sample parameters the user has specified.
 
@@ -239,7 +239,7 @@ The filter module is the second step in the metaQuantome workflow. The filter mo
 >
 {: .question}
 
-##  *metaQuantome: stat*
+##  metaQuantome: stat
 
 > <hands-on-title>Statistical analysis of the filtered data on multiple conditions.</hands-on-title>
 >
@@ -262,13 +262,13 @@ The filter module is the second step in the metaQuantome workflow. The filter mo
 >
 {: .hands_on}
 
-# **Visualize your Data**
+# Visualize your Data
 
 The  outputs of the visualization module of metaQuantome are high-quality, publication-ready visualizations: barplots for the analysis of a single sample or experimental condition and differential abundance analysis, volcano plots, heatmaps, and principal components analysis for comparisons between two or more experimental conditions.
 Here were are showing 2 visualizations: **Barplot and Volcano Plot**. The Heatmap and PCA plot for multiple conditions are under development.
 There are two outputs of the visualization tool : an **HTML file (figure) and a tabular output containing the plot data**.
 
-## *metaQuantome: visualize* Bar Chart
+## metaQuantome: visualize Bar Chart
 
 > <hands-on-title>Bar chart visualization of Functions in T2 sample.</hands-on-title>
 >
@@ -337,7 +337,7 @@ There are two outputs of the visualization tool : an **HTML file (figure) and a
 {: .hands_on}
 ![T7_MF](../../images/T7-mf.png "Top five differentially expressed Molecular Function GO terms for sample T7."){: width="85%"}
 
-## *metaQuantome: visualize* Volcano Plots
+## metaQuantome: visualize Volcano Plots
 
 > <hands-on-title>Volcano Plot visualization of the data T7 and T2.</hands-on-title>
 >

diff --git a/topics/proteomics/tutorials/metaquantome-taxonomy/tutorial.md b/topics/proteomics/tutorials/metaquantome-taxonomy/tutorial.md
@@ -35,7 +35,7 @@ requirements:
        - metaquantome-data-creation
 
 subtopic: multi-omics
-tags: [microbiome]
+tags: [microgalaxy]
 ---
 
 
@@ -58,12 +58,12 @@ To demonstrate the use of this workflow, we have used a thermophilic biogas reac
 {: .agenda}
 
 
-# **Pretreatments**
+# Pretreatments
 
 The first step in this tutorial is to get the data from the Zenodo link provided and make sure that it is in the correct format.
 
 
-## *Get data*
+## Get data
 
 > <hands-on-title>Data upload</hands-on-title>
 >
@@ -91,7 +91,7 @@ The first step in this tutorial is to get the data from the Zenodo link provided
 >
 {: .hands_on}
 
-# **Download metaQuantome Databases**
+# Download metaQuantome Databases
 
 > <hands-on-title>Run metaQuantome databases</hands-on-title>
 >
@@ -132,7 +132,7 @@ The first step in this tutorial is to get the data from the Zenodo link provided
 >
 {: .question}
 
-# **Create metaQuantome sample file**
+# Create metaQuantome sample file
 
 The create samples file module is used to generate the samples file input file for the metaQuantome workflow. This input file is used to specify the column names used for each experimental group. These column names are referenced when handling the input data and performing statistical analysis.
 
@@ -155,10 +155,10 @@ The create samples file module is used to generate the samples file input file f
 {: .hands_on}
 
 
-# **Run metaQuantome**
+# Run metaQuantome
 
 
-## *metaQuantome: expand*
+## metaQuantome: expand
 
 The expand module is the first analysis step in the metaQuantome analysis workflow, and can be run to analyze differently expressed Taxa in the samples.
 In taxonomy mode, the following information is required apart from metaQuantome databases and samples file: a tab-separated taxonomy annotation file, with a peptide column and a taxonomy annotation column. The taxonomic annotations should be the lowest common ancestor (LCA) for each peptide, preferably given as NCBI taxonomy IDs.
@@ -197,7 +197,7 @@ In taxonomy mode, the following information is required apart from metaQuantome
 {: .hands_on}
 
 
-## *metaQuantome: filter*
+## metaQuantome: filter
 
 The filter module is the second step in the metaQuantome workflow. The filter module filters the expanded terms to those that are representative of the data according to the sample parameters the user has specified.
 
@@ -235,7 +235,7 @@ The filter module is the second step in the metaQuantome workflow. The filter mo
 >
 {: .question}
 
-## *metaQuantome: stat*
+## metaQuantome: stat
 
 > <hands-on-title>Statistical analysis of the filtered data on multiple conditions.</hands-on-title>
 >
@@ -259,13 +259,13 @@ The filter module is the second step in the metaQuantome workflow. The filter mo
 {: .hands_on}
 
 
-# **Visualize your Data**
+# Visualize your Data
 
 The  outputs of the visualization module of metaQuantome are high-quality, publication-ready visualizations: barplots for the analysis of a single sample or experimental condition and differential abundance analysis, volcano plots, heatmaps, and principal components analysis for comparisons between two or more experimental conditions.
 Here were are showing 2 visualizations: **Barplot and Volcano Plot**. The Heatmap and PCA plot for multiple conditions are under development.
 There are two outputs of the visualization tool : an **HTML file (figure) and a tabular output containing the plot data**.
 
-## *metaQuantome: visualize*
+## metaQuantome: visualize
 
 > <hands-on-title>Bar chart visualization of Taxonomy in T2 sample.</hands-on-title>
 >
@@ -336,7 +336,7 @@ There are two outputs of the visualization tool : an **HTML file (figure) and a
 
 ![T4_taxa](../../images/T4_taxa.png "Bar Chart visualization of Top 5 genus present in T4 sample."){: width="85%"}
 
-## *metaQuantome: visualize* Volcano Plots
+## metaQuantome: visualize Volcano Plots
 
 > <hands-on-title>Volcano Plot visualization of the data T4 and T2.</hands-on-title>
 >

diff --git a/topics/variant-analysis/tutorials/microbial-variants/tutorial.md b/topics/variant-analysis/tutorials/microbial-variants/tutorial.md
@@ -6,6 +6,7 @@ subtopic: introduction
 zenodo_link: "https://doi.org/10.5281/zenodo.582600"
 tags:
   - prokaryote
+  - microgalaxy
 questions:
   - "How do we detect differences between a set of reads from a microorganism and a reference genome"
 objectives:

diff --git a/topics/variant-analysis/tutorials/non-dip/tutorial.md b/topics/variant-analysis/tutorials/non-dip/tutorial.md
@@ -6,6 +6,7 @@ subtopic: introduction
 zenodo_link: "https://doi.org/10.5281/zenodo.1251112"
 tags:
   - prokaryote
+  - microgalaxy
 questions:
   - "How does frequency of mitochondrial polymorphisms change from mother to child?"
 objectives: