From 3289cfe91a458141172422b20ad435ee91eb523e Mon Sep 17 00:00:00 2001 From: Saskia Hiltemann Date: Wed, 25 Sep 2024 09:36:34 +0000 Subject: [PATCH 01/13] add new recording from Google Form submission --- .../tutorials/amr-gene-detection/tutorial.md | 41 ++++++++++++------- 1 file changed, 26 insertions(+), 15 deletions(-) diff --git a/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md b/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md index 5f3008d169f6c2..4b70de1cc20895 100644 --- a/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md +++ b/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md @@ -1,19 +1,19 @@ --- layout: tutorial_hands_on - title: Identification of AMR genes in an assembled bacterial genome -zenodo_link: 'https://zenodo.org/record/10572227' +zenodo_link: https://zenodo.org/record/10572227 questions: - Which resistance genes are on a bacterial genome? - Where are the genes located on the genome? objectives: - Run a series of tool to assess the presence of antimicrobial resistance genes (ARG) -- Get information about ARGs +- Get information about ARGs - Visualize the ARGs and plasmid genes in their genomic context time_estimation: 2h key_points: - staramr is a powerful tool to predict ARGs and plasmid genes -- Visualization of the ARGs and plasmid genes in their genomic context helps to make sense of the data +- Visualization of the ARGs and plasmid genes in their genomic context helps to make + sense of the data tags: - gmod - illumina @@ -23,15 +23,14 @@ tags: - microgalaxy subtopic: prokaryote edam_ontology: -- topic_3673 # Whole genome sequencing -- topic_3305 # Public health and epidemiology -- topic_0622 # Genomics -- topic_3301 # Microbiology -- topic_0080 # Sequence analysis -- topic_3324 # Infectious disease -- topic_4013 # Antimicrobial resistance +- topic_3673 +- topic_3305 +- topic_0622 +- topic_3301 +- topic_0080 +- topic_3324 +- topic_4013 level: Introductory - contributions: authorship: - bazante1 @@ -44,18 +43,30 @@ contributions: funding: - avans-atgm - abromics - follow_up_training: -- type: "internal" +- type: internal topic_name: visualisation tutorials: - jbrowse -- type: "internal" +- type: internal topic_name: galaxy-interface tutorials: - history-to-workflow +recordings: +- youtube_id: TODO + length: 26M + galaxy_version: 24.1.2.dev0 + date: '2024-09-24' + speakers: + - SaimMomin12 + captioners: + - SaimMomin12 + bot-timestamp: 1727199012 + + --- + Antimicrobial resistance (AMR) is a global phenomenon with no geographical or species boundaries, which poses an important threat to human, animal and environmental health. It is a complex and growing problem that compromises our ability to treat bacterial infections. AMR gene content can be assessed from whole genome sequencing to detect known resistance mechanisms and potentially identify novel mechanisms. From 0ececf29558cf80398e8b3140764d8f6ec1554b0 Mon Sep 17 00:00:00 2001 From: Deepti Varshney <44775741+Deeptivarshney@users.noreply.github.com> Date: Wed, 25 Sep 2024 13:46:26 +0200 Subject: [PATCH 02/13] Update topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md --- .../genome-annotation/tutorials/amr-gene-detection/tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md b/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md index 4b70de1cc20895..a4c6fb76da2330 100644 --- a/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md +++ b/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md @@ -53,7 +53,7 @@ follow_up_training: tutorials: - history-to-workflow recordings: -- youtube_id: TODO +- youtube_id: hfiYCIcD0ww length: 26M galaxy_version: 24.1.2.dev0 date: '2024-09-24' From e5c211177aeab86887f3d789dfbbc872f9953143 Mon Sep 17 00:00:00 2001 From: Saskia Hiltemann Date: Wed, 25 Sep 2024 13:56:12 +0200 Subject: [PATCH 03/13] restore comments --- .../tutorials/amr-gene-detection/tutorial.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md b/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md index a4c6fb76da2330..fd77f245dcc2a7 100644 --- a/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md +++ b/topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md @@ -23,13 +23,13 @@ tags: - microgalaxy subtopic: prokaryote edam_ontology: -- topic_3673 -- topic_3305 -- topic_0622 -- topic_3301 -- topic_0080 -- topic_3324 -- topic_4013 +- topic_3673 # Whole genome sequencing +- topic_3305 # Public health and epidemiology +- topic_0622 # Genomics +- topic_3301 # Microbiology +- topic_0080 # Sequence analysis +- topic_3324 # Infectious disease +- topic_4013 # Antimicrobial resistance level: Introductory contributions: authorship: From d502745e5570ee7883b0f7e5b0fdb8933d5a050c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 26 Sep 2024 09:40:07 +0000 Subject: [PATCH 04/13] Bump webrick from 1.8.1 to 1.8.2 Bumps [webrick](https://github.com/ruby/webrick) from 1.8.1 to 1.8.2. - [Release notes](https://github.com/ruby/webrick/releases) - [Commits](https://github.com/ruby/webrick/compare/v1.8.1...v1.8.2) --- updated-dependencies: - dependency-name: webrick dependency-type: direct:production ... Signed-off-by: dependabot[bot] --- Gemfile.lock | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Gemfile.lock b/Gemfile.lock index 74f96469c95bac..417dd1e86c7e42 100644 --- a/Gemfile.lock +++ b/Gemfile.lock @@ -110,7 +110,7 @@ GEM typhoeus (1.4.0) ethon (>= 0.9.0) unicode-display_width (2.5.0) - webrick (1.8.1) + webrick (1.8.2) yell (2.2.2) zeitwerk (2.6.12) From 4d8a360f205836174d829b778c0198fa3ced1eb6 Mon Sep 17 00:00:00 2001 From: Helena Rasche Date: Thu, 26 Sep 2024 11:49:37 +0200 Subject: [PATCH 05/13] Fix remaining broken boxes since our checker stopped working --- .../tutorials/vgp_genome_assembly/tutorial.md | 137 ++++++++--------- .../community-tool-table/tutorial.md | 11 +- .../dev/tutorials/tool-annotation/tutorial.md | 4 +- .../tutorials/tool-from-scratch/tutorial.md | 2 +- .../fair-data-registration/tutorial.md | 4 +- .../tutorial.md | 3 +- .../tutorial.md | 2 +- .../tutorial.md | 3 + .../tutorial.md | 10 +- .../tutorial.md | 6 +- .../tutorials/beacon_cnv_query/tutorial.md | 48 +++--- .../tutorials/beaconise_1000hg/tutorial.md | 142 +++++++++--------- 12 files changed, 190 insertions(+), 182 deletions(-) diff --git a/topics/assembly/tutorials/vgp_genome_assembly/tutorial.md b/topics/assembly/tutorials/vgp_genome_assembly/tutorial.md index 0c64418270c5f9..ef50d16210f0c6 100644 --- a/topics/assembly/tutorials/vgp_genome_assembly/tutorial.md +++ b/topics/assembly/tutorials/vgp_genome_assembly/tutorial.md @@ -548,34 +548,34 @@ Let's use gfastats to get a basic idea of what our assembly looks like. We'll ru > > 2. Rename outputs of `gfastats` step to as `Hap1 stats` and `Hap2 stats` > -> > > This would generate summary files that look like this (only the first six rows are shown): -> > > -> > > ``` -> > > Expected genome size 11747160 -> > > # scaffolds 0 -> > > Total scaffold length 0 -> > > Average scaffold length nan -> > > Scaffold N50 0 -> > > Scaffold auN 0.00 -> > > ``` -> > > -> > > Because we ran `gfastats` on hap1 and hap2 outputs of `hifiasm` we need to join the two outputs together for easier interpretation: +> This would generate summary files that look like this (only the first six rows are shown): +> +> ``` +> Expected genome size 11747160 +> # scaffolds 0 +> Total scaffold length 0 +> Average scaffold length nan +> Scaffold N50 0 +> Scaffold auN 0.00 +> ``` +> +> Because we ran `gfastats` on hap1 and hap2 outputs of `hifiasm` we need to join the two outputs together for easier interpretation: > > 3. Run {% tool [Column join](toolshed.g2.bx.psu.edu/repos/iuc/collection_column_join/collection_column_join/0.0.3) %} with the following parameters: > - {% icon param-files %} *"Input file"*: select `Hap1 stats` and the `Hap2 stats` datasets. Keep all other settings as they are. > > 4. Rename the output as `gfastats on hap1 and hap2 (full)` > -> > > This would generate a joined summary file that looks like this (only the first five rows are shown): -> > > -> > > ``` -> > > # gaps 0 0 -> > > # gaps in scaffolds 0 0 -> > > # paths 0 0 -> > > # segments 17 16 -> > > ``` -> > > -> > > Now let's extract only relevant information by excluding all lines containing the word `scaffold` since there are no scaffolds at this stage of the assembly process (only contigs): +> This would generate a joined summary file that looks like this (only the first five rows are shown): +> +> ``` +> # gaps 0 0 +> # gaps in scaffolds 0 0 +> # paths 0 0 +> # segments 17 16 +> ``` +> +> Now let's extract only relevant information by excluding all lines containing the word `scaffold` since there are no scaffolds at this stage of the assembly process (only contigs): > > 5. Run {% tool [Search in textfiles](toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1) %} with the following parameters: > - {% icon param-files %} *"Input file"*: select `gfastats on hap1 and hap2 (full)` @@ -756,35 +756,35 @@ Let's use gfastats to get a basic idea of what our assembly looks like. We'll ru > > 2. Rename outputs of `gfastats` step to as `Primary stats` and `Alternate stats` > -> > > This would generate summary files that look like this (only the first six rows are shown): -> > > -> > > ``` -> > > Expected genome size 11747160 -> > > # scaffolds 25 -> > > Total scaffold length 18519764 -> > > Average scaffold length 740790.56 -> > > Scaffold N50 813311 -> > > Scaffold auN 913050.77 -> > > ``` -> > > -> > > Because we ran `gfastats` on Primary and Alternate outputs of `hifiasm` we need to join the two outputs together for easier interpretation: +> This would generate summary files that look like this (only the first six rows are shown): +> +> ``` +> Expected genome size 11747160 +> # scaffolds 25 +> Total scaffold length 18519764 +> Average scaffold length 740790.56 +> Scaffold N50 813311 +> Scaffold auN 913050.77 +> ``` +> +> Because we ran `gfastats` on Primary and Alternate outputs of `hifiasm` we need to join the two outputs together for easier interpretation: > > 3. Run {% tool [Column join](toolshed.g2.bx.psu.edu/repos/iuc/collection_column_join/collection_column_join/0.0.3) %} with the following parameters: > - {% icon param-files %} *"Input file"*: select `Primary stats` and the `Alternate stats` datasets (these are from **Step 2** above). Keep all other setting as they are. > > 4. Rename the output as `gfastats on Pri and Alt (full)` > -> > > This would generate a joined summary file that looks like this (only five rows are shown): -> > > -> > > ``` -> > > # contigs 25 10 -> > > # dead ends . 16 -> > > # disconnected components . 7 -> > > # edges . 6 -> > > # gaps 0 0 -> > > ``` -> > > -> > > Now let's extract only relevant information by excluding all lines containing the word `scaffold` since there are no scaffolds at this stage of the assembly process (only contigs): +> This would generate a joined summary file that looks like this (only five rows are shown): +> +> ``` +> # contigs 25 10 +> # dead ends . 16 +> # disconnected components . 7 +> # edges . 6 +> # gaps 0 0 +> ``` +> +> Now let's extract only relevant information by excluding all lines containing the word `scaffold` since there are no scaffolds at this stage of the assembly process (only contigs): > > 5. Run {% tool [Search in textfiles](toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1) %} with the following parameters: > - {% icon param-files %} *"Input file"*: select `gfastats on Pri and Alt (full)` @@ -876,7 +876,7 @@ Despite BUSCO being robust for species that have been widely studied, it can be > - {% icon param-file %} *"First genome assembly"*: `Primary contigs FASTA` > - {% icon param-file %} *"Second genome assembly"*: `Alternate contigs FASTA` > -> > > (REMINDER: `Primary contigs FASTA` and `Alternate contigs FASTA` were generated [earlier](#gfa2fasta_solo)) +> (REMINDER: `Primary contigs FASTA` and `Alternate contigs FASTA` were generated [earlier](#gfa2fasta_solo)) > {: .hands_on} @@ -913,23 +913,24 @@ The first relevant parameter is the `Estimated genome size`. > Get estimated genome size > > 1. Look at the `GenomeScope summary` output (generated during *k*-mer profiling [step](#genome-profiling-with-genomescope2)). The file should have content that looks like this (it may not be exactly like this): -> > ``` -> > GenomeScope version 2.0 -> > input file = .... -> > output directory = . -> > p = 2 -> > k = 31 -> > TESTING set to TRUE -> > -> > property min max -> > Homozygous (aa) 99.4165% 99.4241% -> > Heterozygous (ab) 0.575891% 0.583546% -> > Genome Haploid Length 11,739,321 bp 11,747,160 bp -> > Genome Repeat Length 722,921 bp 723,404 bp -> > Genome Unique Length 11,016,399 bp 11,023,755 bp -> > Model Fit 92.5159% 96.5191% -> > Read Error Rate 0.000943206% 0.000943206% -> > ``` +> +> ``` +> GenomeScope version 2.0 +> input file = .... +> output directory = . +> p = 2 +> k = 31 +> TESTING set to TRUE +> +> property min max +> Homozygous (aa) 99.4165% 99.4241% +> Heterozygous (ab) 0.575891% 0.583546% +> Genome Haploid Length 11,739,321 bp 11,747,160 bp +> Genome Repeat Length 722,921 bp 723,404 bp +> Genome Unique Length 11,016,399 bp 11,023,755 bp +> Model Fit 92.5159% 96.5191% +> Read Error Rate 0.000943206% 0.000943206% +> ``` > > 2. Copy the number value for the maximum Genome Haploid Length to your clipboard (CTRL + C on Windows; CMD + C on MacOS). > 3. Click on "Upload Data" in the toolbox on the left. @@ -992,7 +993,7 @@ Now let's parse the `transition between haploid & diploid` and `upper bound for > > > {: .question} > -> > Now let's get the transition parameter. +> Now let's get the transition parameter. > > 5. Run {% tool [Advanced Cut](toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cut_tool/1.1.0) %} with the following parameters: > - {% icon param-file %} *"File to cut"*: `Parsing purge parameters` @@ -1318,11 +1319,11 @@ Before we begin, we need to upload BioNano data: > > 1. Copy the following URLs into clipboard. You can do this by clicking on {% icon copy %} button in the right upper corner of the box below. It will appear if you mouse over the box. > -> > ``` -> > https://zenodo.org/records/5887339/files/bionano.cmap -> > ``` +> ``` +> https://zenodo.org/records/5887339/files/bionano.cmap +> ``` > -> 2. Upload datasets into Galaxy +> 2. Upload datasets into Galaxy > - set the datatype to `cmap` > > {% snippet faqs/galaxy/datasets_import_via_link.md format="cmap" %} diff --git a/topics/dev/tutorials/community-tool-table/tutorial.md b/topics/dev/tutorials/community-tool-table/tutorial.md index 79871b679d6ab3..3dd8bfd945901f 100644 --- a/topics/dev/tutorials/community-tool-table/tutorial.md +++ b/topics/dev/tutorials/community-tool-table/tutorial.md @@ -130,14 +130,17 @@ an example of the file that is used to manually filter the tools for a community > 1. Download the `tools.tsv` file in `results/`. > 2. Open `tools.tsv` with a Spreadsheet Software. > 3. Review each line corresponding to a tool - - You can also just review some tools. Those tools that are not reviewed will be have `FALSE` in the `Reviewed` columns the updated table. +> +> You can also just review some tools. Those tools that are not reviewed will be have `FALSE` in the `Reviewed` columns the updated table. +> > 1. Change the value in the `Reviewed` column from `FALSE` to `TRUE` (this will be done automatically if an entry of the tool in `tools_status.tsv` exists). > 2. Add `TRUE` to the `To keep` column if the tool should be kept, and `FALSE` if not. > 3. Add `TRUE` or `FALSE` also to the `Deprecated` column. +> > 4. Copy paste the `Galaxy wrapper id`, `To keep`, `Deprecated` column in a new table (in that order). - - This can also be done using the reference function of your Spreadsheet Software. +> +> This can also be done using the reference function of your Spreadsheet Software. +> > 5. Export the new table as TSV (without header). > 6. Submit the TSV as `tools_status.tsv` in your community folder. > 7. Wait for the Pull Request to be merged diff --git a/topics/dev/tutorials/tool-annotation/tutorial.md b/topics/dev/tutorials/tool-annotation/tutorial.md index 9215bbc1b72bce..f2ebf4e609a045 100644 --- a/topics/dev/tutorials/tool-annotation/tutorial.md +++ b/topics/dev/tutorials/tool-annotation/tutorial.md @@ -188,7 +188,7 @@ To link a Galaxy tool to its corresponding bio.tools entry, we need to first fin > 2. Search your tool > 3. Expand the row > 4. Open the link shown in the `Galaxy wrapper parsed folder` column - +> {: .hands_on} Now we have the wrapper, and can add the bio.tools entry. @@ -214,4 +214,4 @@ Now we have the wrapper, and can add the bio.tools entry. > {: .hands_on} -# Conclusion \ No newline at end of file +# Conclusion diff --git a/topics/dev/tutorials/tool-from-scratch/tutorial.md b/topics/dev/tutorials/tool-from-scratch/tutorial.md index 3bbcd56589aac7..694c0c8932e2ad 100644 --- a/topics/dev/tutorials/tool-from-scratch/tutorial.md +++ b/topics/dev/tutorials/tool-from-scratch/tutorial.md @@ -462,7 +462,7 @@ Note that for using `planemo`from a new shell you will need to activate the pyth > > ```bash > > planemo, version 0.74.3 > > ``` -> {: .code-out} +> {: .code-in} > > 2. `planemo --help` will show the available commands with a short desctiption (lint, test, and serve will be part of this tutorial) > 3. `planemo SUBCOMMAND --help` will show the usage information for the corresponding subcommand. Try to obtain the information for the `lint` subcommand. diff --git a/topics/fair/tutorials/fair-data-registration/tutorial.md b/topics/fair/tutorials/fair-data-registration/tutorial.md index 72a25f0adada44..ac2e637302433c 100644 --- a/topics/fair/tutorials/fair-data-registration/tutorial.md +++ b/topics/fair/tutorials/fair-data-registration/tutorial.md @@ -109,7 +109,7 @@ Discipline-specific repositories cater for communities and datatypes, and typica > > > An example of a discipline-specific repository is [ArrayExpress](https://www.ebi.ac.uk/biostudies/arrayexpress) database. ArrayExpress stores data from high-through functional genomics assays, such as RNAseq, ChIPseq and expression microarrays. -The data submission interface of ArrayExpress is called [Annotare](https://www.ebi.ac.uk/fg/annotare/login/). Without creating a login, what help is given to a person looking to submit a dataset for the first time? +> The data submission interface of ArrayExpress is called [Annotare](https://www.ebi.ac.uk/fg/annotare/login/). Without creating a login, what help is given to a person looking to submit a dataset for the first time? > > > > > @@ -127,7 +127,7 @@ The data submission interface of ArrayExpress is called [Annotare](https://www.e > > > > > > Open the **Findability** pulldown on the left hand banner to find recipes for the following: -[Depositing to generic repositories - Zenodo use case](https://faircookbook.elixir-europe.org/content/recipes/findability/zenodo-deposition.html) and [Registering Datasets in Wikidata](https://faircookbook.elixir-europe.org/content/recipes/findability/registeringDatasets.html). +> > [Depositing to generic repositories - Zenodo use case](https://faircookbook.elixir-europe.org/content/recipes/findability/zenodo-deposition.html) and [Registering Datasets in Wikidata](https://faircookbook.elixir-europe.org/content/recipes/findability/registeringDatasets.html). > > > {: .solution} {: .question} diff --git a/topics/fair/tutorials/ro-crate-galaxy-best-practices/tutorial.md b/topics/fair/tutorials/ro-crate-galaxy-best-practices/tutorial.md index 057b8ef82ddba0..05345b949f0a9c 100644 --- a/topics/fair/tutorials/ro-crate-galaxy-best-practices/tutorial.md +++ b/topics/fair/tutorials/ro-crate-galaxy-best-practices/tutorial.md @@ -34,8 +34,7 @@ Providing documentation is also important to help understand the workflow's purp > > -> In this tutorial, you will learn about the best practices that the Galaxy community -has created for workflows. +> In this tutorial, you will learn about the best practices that the Galaxy community has created for workflows. > > 1. TOC > {:toc} diff --git a/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md b/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md index 82bc02c345e744..0fde73815a8517 100644 --- a/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md +++ b/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md @@ -104,7 +104,7 @@ E.g. the workflow could be combined with metagenomic workflows, that allow to sc > > Genome download > > > > This downloads the `Streptomyces coelicolor A3(2) complete genome`, -which should be a great source for biosynthetic gene clusters (BGCs). +> > which should be a great source for biosynthetic gene clusters (BGCs). > {: .comment} > {: .hands_on} diff --git a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md index c9bf3ba522b03f..a2d3e8e1178e38 100644 --- a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md +++ b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md @@ -783,6 +783,7 @@ To prepare the **ABRicate**{% icon tool %} output tabulars of both samples for f
+> Antimicrobial Resistance Genes Identification > 1. {% tool [Replace](toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4) %} with the following parameters: > - {% icon param-file %} *"File to process"*: `report` (output of **ABRicate** {% icon tool %}) > - In *"Find and Replace"*: @@ -803,6 +804,7 @@ To prepare the **ABRicate**{% icon tool %} output tabulars of both samples for f > > 2. Rename the output collection `AMRs` {: .hands-on} +
> @@ -874,6 +876,7 @@ To prepare the **ABRicate**{% icon tool %} output tabulars of both samples for f
+> Replace Text > 1. {% tool [Replace](toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4) %} with the following parameters: > - {% icon param-file %} *"File to process"*: `report` (output of **ABRicate** {% icon tool %}) > - In *"Find and Replace"*: 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 a7660669da7187..12ef70a8ac2a4d 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 @@ -169,11 +169,11 @@ You can access the data for this tutorial in multiple ways: > - {% icon param-file %} *"Annotated data matrix"*: `N701-400k` > - *"Function to manipulate the object"*: `Concatenate along the observations axis` > - {% icon param-file %} *"Annotated data matrix to add"*: `Select all the other matrix files from bottom to top, N702 to N707` -> -> -> >If you imported files from Zenodo instead of using the input history, yours might not be in the same order as ours. Since the files will be concatenated in the order that you click, it will be helpful if you click them in the same order, from N702 to N707. This will ensure your samples are given the same batch numbers as we got in this tutorial, which will help when we're adding in metadata later! - {: .comment} -> +> +> > +> > If you imported files from Zenodo instead of using the input history, yours might not be in the same order as ours. Since the files will be concatenated in the order that you click, it will be helpful if you click them in the same order, from N702 to N707. This will ensure your samples are given the same batch numbers as we got in this tutorial, which will help when we're adding in metadata later! +> {: .comment} +> > > Don't add N701! > > You are adding files to N701, so do not add N701 to itself! > {: .warning} diff --git a/topics/transcriptomics/tutorials/differential-isoform-expression/tutorial.md b/topics/transcriptomics/tutorials/differential-isoform-expression/tutorial.md index cc3344a78430a7..c3baebd597f86f 100644 --- a/topics/transcriptomics/tutorials/differential-isoform-expression/tutorial.md +++ b/topics/transcriptomics/tutorials/differential-isoform-expression/tutorial.md @@ -131,10 +131,12 @@ Next we will retrieve the remaining datasets. > {: .hands_on} - +{: .details} +--> # Quality assessment diff --git a/topics/variant-analysis/tutorials/beacon_cnv_query/tutorial.md b/topics/variant-analysis/tutorials/beacon_cnv_query/tutorial.md index 8e13fd30effed9..11113bb2ce83fb 100644 --- a/topics/variant-analysis/tutorials/beacon_cnv_query/tutorial.md +++ b/topics/variant-analysis/tutorials/beacon_cnv_query/tutorial.md @@ -86,30 +86,30 @@ Those parametars are, "CHROMOSOME", "Start", and "End". > > > > What types of information can be extracted from records? > > -> > > ```json -> > >{'_id': ObjectId('66c466431ea6cb4184ee0f2f'), -> > > 'assemblyId': 'GRCh38', -> > > 'biosampleId': 'MP2PRT-PARNFH-TMP1-A, MP2PRT-PARNFH-NM1-A', -> > > 'definitions': {'Location': {'chromosome': '17', -> > > 'end': 43170245, -> > > 'start': 43044295}}, -> > > 'diseaseType': 'acute lymphoblastic leukemia', -> > > 'gene': 'BRCA1', -> > > 'geneID': 'ENSG00000012048.23', -> > > 'id': 'refvar-66c466431ea6cb4184ee0f2f', -> > > 'info': {'caseID': 'MP2PRT-PARNFH, MP2PRT-PARNFH', -> > > 'cnCount': 3, -> > > 'fileName': 'f11b7fb7-a610-4978-b5c4-523450a0fd5f.wgs.ASCAT.gene_level.copy_number_variation.tsv', -> > > 'legacyId': 'DUP:chr17:43044295-43170245', -> > > 'projectID': 'MP2PRT-ALL', -> > > 'sampleType': 'Blood Derived Cancer - Bone Marrow, Blood Derived ' -> > > 'Cancer - Bone Marrow, Post-treatment'}, -> > > 'primarySite': 'hematopoietic and reticuloendothelial systems', -> > > 'updated': '2024-08-19T21:23:09.374531', -> > > 'variantInternalId': '17:43044295-43170245:EFO:0030071', -> > > 'variantState': {'id': 'EFO:0030071', 'label': 'low-level gain'}, -> > > 'variantType': 'DUP'} -> > > ``` +> > ```json +> > {'_id': ObjectId('66c466431ea6cb4184ee0f2f'), +> > 'assemblyId': 'GRCh38', +> > 'biosampleId': 'MP2PRT-PARNFH-TMP1-A, MP2PRT-PARNFH-NM1-A', +> > 'definitions': {'Location': {'chromosome': '17', +> > 'end': 43170245, +> > 'start': 43044295}}, +> > 'diseaseType': 'acute lymphoblastic leukemia', +> > 'gene': 'BRCA1', +> > 'geneID': 'ENSG00000012048.23', +> > 'id': 'refvar-66c466431ea6cb4184ee0f2f', +> > 'info': {'caseID': 'MP2PRT-PARNFH, MP2PRT-PARNFH', +> > 'cnCount': 3, +> > 'fileName': 'f11b7fb7-a610-4978-b5c4-523450a0fd5f.wgs.ASCAT.gene_level.copy_number_variation.tsv', +> > 'legacyId': 'DUP:chr17:43044295-43170245', +> > 'projectID': 'MP2PRT-ALL', +> > 'sampleType': 'Blood Derived Cancer - Bone Marrow, Blood Derived ' +> > 'Cancer - Bone Marrow, Post-treatment'}, +> > 'primarySite': 'hematopoietic and reticuloendothelial systems', +> > 'updated': '2024-08-19T21:23:09.374531', +> > 'variantInternalId': '17:43044295-43170245:EFO:0030071', +> > 'variantState': {'id': 'EFO:0030071', 'label': 'low-level gain'}, +> > 'variantType': 'DUP'} +> > ``` > > > > > > > > 1. Identifiers and IDs: diff --git a/topics/variant-analysis/tutorials/beaconise_1000hg/tutorial.md b/topics/variant-analysis/tutorials/beaconise_1000hg/tutorial.md index 58a383a6c9f5cb..bc8f7449ad4e7a 100644 --- a/topics/variant-analysis/tutorials/beaconise_1000hg/tutorial.md +++ b/topics/variant-analysis/tutorials/beaconise_1000hg/tutorial.md @@ -109,45 +109,45 @@ We will use docker and docker-compose for this step. If you don't have it instal > nano docker-compose.yaml > ``` > 4. Copy the text below into the `docker-compose.yaml` file -> >```yaml -> > version: '3.6' -> > services: -> > -> > mongo-client: -> > image: mongo:3.6 -> > restart: unless-stopped -> > volumes: -> > - ./mongo/db:/data/db -> > - ./mongo-init:/docker-entrypoint-initdb.d -> > ports: -> > - "27017:27017" -> > environment: -> > MONGO_INITDB_ROOT_USERNAME: root -> > MONGO_INITDB_ROOT_PASSWORD: example -> > -> > mongo-express: -> > image: mongo-express -> > restart: unless-stopped -> > environment: -> > - ME_CONFIG_MONGODB_SERVER=mongo-client -> > - ME_CONFIG_MONGODB_PORT=27017 -> > - ME_CONFIG_BASICAUTH_USERNAME=root -> > - ME_CONFIG_BASICAUTH_PASSWORD=example -> > ports: -> > - "8081:8081" -> > -> > mongo-init: -> > image: mongo:3.6 -> > restart: "no" -> > depends_on: -> > - mongo-client -> > environment: -> > - MONGO_INITDB_DATABASE=admin -> > - MONGO_INITDB_ROOT_USERNAME=root -> > - MONGO_INITDB_ROOT_PASSWORD=example -> > volumes: -> > - ./mongo-init:/docker-entrypoint-initdb.d -> > ``` +> ```yaml +> version: '3.6' +> services: +> +> mongo-client: +> image: mongo:3.6 +> restart: unless-stopped +> volumes: +> - ./mongo/db:/data/db +> - ./mongo-init:/docker-entrypoint-initdb.d +> ports: +> - "27017:27017" +> environment: +> MONGO_INITDB_ROOT_USERNAME: root +> MONGO_INITDB_ROOT_PASSWORD: example +> +> mongo-express: +> image: mongo-express +> restart: unless-stopped +> environment: +> - ME_CONFIG_MONGODB_SERVER=mongo-client +> - ME_CONFIG_MONGODB_PORT=27017 +> - ME_CONFIG_BASICAUTH_USERNAME=root +> - ME_CONFIG_BASICAUTH_PASSWORD=example +> ports: +> - "8081:8081" +> +> mongo-init: +> image: mongo:3.6 +> restart: "no" +> depends_on: +> - mongo-client +> environment: +> - MONGO_INITDB_DATABASE=admin +> - MONGO_INITDB_ROOT_USERNAME=root +> - MONGO_INITDB_ROOT_PASSWORD=example +> volumes: +> - ./mongo-init:/docker-entrypoint-initdb.d +> ``` > 5. Create the path `mongo/db` in your directory using `$mkdir` tool > ```bash > mkdir mongo @@ -168,23 +168,23 @@ We will use docker and docker-compose for this step. If you don't have it instal > nano create-user.js > ``` > 9. Copy the text below into the `create-user.js` file -> >```js -> > // create_user.js -> > -> > // Connect to the admin database -> > var adminDB = db.getSiblingDB("admin"); -> > -> > // Create a new user with read-only access to all databases -> > adminDB.createUser({ -> > user: "query_user", -> > pwd: "querypassword", -> > roles: [ -> > { role: "read", db: "admin" }, -> > { role: "read", db: "Beacon" }, // Adjust this for your needs -> > // Add additional read roles as needed -> > ] -> >}); -> > ``` +> ```js +> // create_user.js +> +> // Connect to the admin database +> var adminDB = db.getSiblingDB("admin"); +> +> // Create a new user with read-only access to all databases +> adminDB.createUser({ +> user: "query_user", +> pwd: "querypassword", +> roles: [ +> { role: "read", db: "admin" }, +> { role: "read", db: "Beacon" }, // Adjust this for your needs +> // Add additional read roles as needed +> ] +> }); +> ``` > This will add a user (user name: `query_user` and password:`querypassword`) account with read-only permission to the Beacon database. This is important to avoid unwanted modifications to the Beacon database. > To know more about MongoDB, please read the [MongoDB documentation](https://www.mongodb.com/docs/). > 10. Run the command `$docker-compose` in the directory containing the `docker-compose.yaml` file with the specified parameters. @@ -456,21 +456,21 @@ We are looking to see if there is a deletion mutation in the gene **located** in > - *"END"*: `243620819` > - *"VARIANT STATE ID"*: `EFO:0030068` > The srarch function will queiry the Beacon database and print out the resutls that matches our quiery specifications. In this case it will print something like this. -> > ```json -> > {'_id': ObjectId('6690160a3a936e8e0a7828e2'), -> > 'assemblyId': 'GRCh38', -> > 'biosampleId': 'HG00096', -> > 'definitions': {'Location': {'chromosome': '1', -> > 'end': 243620819, -> > 'start': 243618689}}, -> > 'id': 'refvar-6690160a3a936e8e0a7828e2', -> > 'info': {'cnCount': 1, -> > 'cnValue': 0.422353, -> > 'legacyId': 'DRAGEN:LOSS:chr1:243618690-243620819'}, -> > 'updated': '2024-07-11T17:26:27.265115', -> > 'variantInternalId': 'chr1:243618689-243620819:EFO:0030068', -> > 'variantState': {'id': 'EFO:0030068', 'label': 'low-level loss'}} -> > ``` +> ```json +> {'_id': ObjectId('6690160a3a936e8e0a7828e2'), +> 'assemblyId': 'GRCh38', +> 'biosampleId': 'HG00096', +> 'definitions': {'Location': {'chromosome': '1', +> 'end': 243620819, +> 'start': 243618689}}, +> 'id': 'refvar-6690160a3a936e8e0a7828e2', +> 'info': {'cnCount': 1, +> 'cnValue': 0.422353, +> 'legacyId': 'DRAGEN:LOSS:chr1:243618690-243620819'}, +> 'updated': '2024-07-11T17:26:27.265115', +> 'variantInternalId': 'chr1:243618689-243620819:EFO:0030068', +> 'variantState': {'id': 'EFO:0030068', 'label': 'low-level loss'}} +> ``` > > When sharing a Beacon protocol, it is important to provide users with read-only access to query the Beacon database. Creating read-only users for Beacon-providing institutions helps prevent unwanted data overwrites that can occur by mistake. > From 49863b233d4b59f650a075747335e057a8aa8f45 Mon Sep 17 00:00:00 2001 From: Helena Rasche Date: Thu, 26 Sep 2024 11:57:26 +0200 Subject: [PATCH 06/13] fix json ld failures cc #5362 --- topics/community/tutorials/sig_define/tutorial.md | 6 ++---- .../tutorials/tool-generators-advanced/tutorial.md | 10 ++++------ .../single-cell/tutorials/GO-enrichment/tutorial.md | 12 +++++------- 3 files changed, 11 insertions(+), 17 deletions(-) diff --git a/topics/community/tutorials/sig_define/tutorial.md b/topics/community/tutorials/sig_define/tutorial.md index 73568c7f62110a..a1498195a27b8e 100644 --- a/topics/community/tutorials/sig_define/tutorial.md +++ b/topics/community/tutorials/sig_define/tutorial.md @@ -37,6 +37,8 @@ follow_up_training: - sig_create --- +In Galaxy, the term *[Special Interest Group](https://galaxyproject.org/community/sig)* (**SIG**) refers to a dedicated scientific community that crosses individual lab boundaries and wants to collaborate, share resources, support each other, and/or collectively advocate on a given theme. We have **SIGs** based on [**region**](https://galaxyproject.org/community/sig/#regional-communities), [**domain of science**](https://galaxyproject.org/community/sig/#communities-of-practice), and more. You might consider that a **SIG** covers any group of like-minded Galaxy enthusiasts not currently combined into a [**Working Group**](https://galaxyproject.org/community/wg/). + > > > In this tutorial, we will cover: @@ -46,10 +48,6 @@ follow_up_training: > {: .agenda} -# Special Interest Groups - -In Galaxy, the term *[Special Interest Group](https://galaxyproject.org/community/sig)* (**SIG**) refers to a dedicated scientific community that crosses individual lab boundaries and wants to collaborate, share resources, support each other, and/or collectively advocate on a given theme. We have **SIGs** based on [**region**](https://galaxyproject.org/community/sig/#regional-communities), [**domain of science**](https://galaxyproject.org/community/sig/#communities-of-practice), and more. You might consider that a **SIG** covers any group of like-minded Galaxy enthusiasts not currently combined into a [**Working Group**](https://galaxyproject.org/community/wg/). -
Person looking at a diagram with a central rectangle connected to many other nodes representing people and connections
You can find a directory of current [**SIGs** below](https://galaxyproject.org/community/sig/). diff --git a/topics/dev/tutorials/tool-generators-advanced/tutorial.md b/topics/dev/tutorials/tool-generators-advanced/tutorial.md index 1d33bba701100c..6c6bd0c8fa143b 100644 --- a/topics/dev/tutorials/tool-generators-advanced/tutorial.md +++ b/topics/dev/tutorials/tool-generators-advanced/tutorial.md @@ -51,6 +51,10 @@ recordings: --- +Galaxy users who write and share scripts useful for scientific analyses are likely to be reading this material, perhaps after seeing the "Hello Galaxy" +demonstration. It was written to help you find out about the capabilities and limits of the ToolFactory by experimenting with it yourself. +It is hoped that this advanced tutorial will introduce some features that potentially make the ToolFactory useful in your work. + > > > 1. TOC @@ -58,12 +62,6 @@ recordings: > {: .agenda} ---- - -Galaxy users who write and share scripts useful for scientific analyses are likely to be reading this material, perhaps after seeing the "Hello Galaxy" -demonstration. It was written to help you find out about the capabilities and limits of the ToolFactory by experimenting with it yourself. -It is hoped that this advanced tutorial will introduce some features that potentially make the ToolFactory useful in your work. - # Background and a user's guide to this training material This training material is unlike most other GTN tutorials. There is no specific tool building curriculum on offer because it is hard to know how diff --git a/topics/single-cell/tutorials/GO-enrichment/tutorial.md b/topics/single-cell/tutorials/GO-enrichment/tutorial.md index 94fa4ada897f6a..7fb0e6343736d9 100644 --- a/topics/single-cell/tutorials/GO-enrichment/tutorial.md +++ b/topics/single-cell/tutorials/GO-enrichment/tutorial.md @@ -37,6 +37,11 @@ contributors: - MennaGamal --- +In the tutorial [Filter, plot and explore single-cell RNA-seq data with Scanpy]({% link topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md %}), we took an important step in our single-cell RNA sequencing analysis by identifying marker genes for each of the clusters in our dataset. These marker genes are crucial, as they help us distinguish between different cell types and states, giving us a clearer picture of the cellular diversity within our samples. +However, simply identifying marker genes is just the beginning. To truly understand what makes each cluster unique, we need to dive deeper into the biological functions these genes are involved in. This is where Gene Ontology (GO) enrichment analysis comes into play. +We will perform GO enrichment analysis as a type of over-representation analysis (ORA), ORA is a statistical method that determines whether genes from pre-defined sets (e.g. genes belonging to a specific GO term) are expressed more than would be expected in a subset of your data. The most commonly used statistical tests are Fischer's exact test and hypergeometric test, more details about them are explained in the tutorial slides. + + > > > In this tutorial, we will cover: @@ -46,13 +51,6 @@ contributors: > {: .agenda} -# Introduction - -In the tutorial [Filter, plot and explore single-cell RNA-seq data with Scanpy]({% link topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.md %}), we took an important step in our single-cell RNA sequencing analysis by identifying marker genes for each of the clusters in our dataset. These marker genes are crucial, as they help us distinguish between different cell types and states, giving us a clearer picture of the cellular diversity within our samples. -However, simply identifying marker genes is just the beginning. To truly understand what makes each cluster unique, we need to dive deeper into the biological functions these genes are involved in. This is where Gene Ontology (GO) enrichment analysis comes into play. -We will perform GO enrichment analysis as a type of over-representation analysis (ORA), ORA is a statistical method that determines whether genes from pre-defined sets (e.g. genes belonging to a specific GO term) are expressed more than would be expected in a subset of your data. The most commonly used statistical tests are Fischer's exact test and hypergeometric test, more details about them are explained in the tutorial slides. - - # Data description In this tutorial will use the following datasets: From 09065d7c6b48905aea99fbb51b96b093c68827ef Mon Sep 17 00:00:00 2001 From: Helena Rasche Date: Thu, 26 Sep 2024 11:58:01 +0200 Subject: [PATCH 07/13] bold unnecessary --- .../tutorials/secondary-metabolite-discovery/tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md b/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md index 0fde73815a8517..e8c441c4231fad 100644 --- a/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md +++ b/topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md @@ -304,7 +304,7 @@ not have a header. {: .hands_on} -## **Remove duplicated molecules** +## Remove duplicated molecules > Remove duplicated molecules > From 5167733be076e5d7640c02fcdafe36866813f60d Mon Sep 17 00:00:00 2001 From: Wolfgang Maier Date: Thu, 26 Sep 2024 15:47:46 +0200 Subject: [PATCH 08/13] Update pangolin version used in SARS-CoV-2 variant discovery tutorial --- .../tutorials/sars-cov-2-variant-discovery/tutorial.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md b/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md index 62e8aa9d7bc89d..7e8b7d3cc43bad 100644 --- a/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md +++ b/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md @@ -266,7 +266,7 @@ Besides the sequenced reads data, we need at least two additional datasets for c > 1. {% tool [Upload](upload1) %} the reference to your history via the link above and make sure the dataset format is set to `fasta`. > > {% snippet faqs/galaxy/datasets_import_via_link.md format="fasta" %} -> 2. {% tool [Replace Text in entire line](toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2) in entire line %} to simplify the reference sequence name +> 2. {% tool [Replace Text in entire line](toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1) in entire line %} to simplify the reference sequence name > - {% icon param-file %} *"File to process"*: the uploaded reference sequence from the ENA > - In {% icon param-repeat %} *"1. Replacement"*: > - *"Find pattern"*: `^>.+` @@ -866,7 +866,7 @@ Pangolin (Phylogenetic Assignment of Named Global Outbreak LINeages) can be used > From consensus sequences to clade assignments using Pangolin > -> 1. {% tool [Pangolin](toolshed.g2.bx.psu.edu/repos/iuc/pangolin/pangolin/4.2+galaxy0) %} with the following parameters: +> 1. {% tool [Pangolin](toolshed.g2.bx.psu.edu/repos/iuc/pangolin/pangolin/4.3+galaxy2) %} with the following parameters: > - {% icon param-file %} *"Input FASTA File(s)"*: `Multisample consensus FASTA` > - *"Include header line in output file"*: `Yes` > From a874c93eaf36eecc42681d0fbbff493a861fb2be Mon Sep 17 00:00:00 2001 From: Wolfgang Maier Date: Thu, 26 Sep 2024 16:17:02 +0200 Subject: [PATCH 09/13] Remove link to outdated zenodo data This data was only used in a former version of the training --- .../tutorials/sars-cov-2-variant-discovery/tutorial.md | 1 - 1 file changed, 1 deletion(-) diff --git a/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md b/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md index 7e8b7d3cc43bad..e0dbc1ef54b58f 100644 --- a/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md +++ b/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md @@ -4,7 +4,6 @@ layout: tutorial_hands_on title: Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data subtopic: one-health level: Intermediate -zenodo_link: "https://zenodo.org/record/5036687" questions: - How can a complete analysis, including viral consensus sequence reconstruction and lineage assignment be performed? - How can such an analysis be kept manageable for lots of samples, yet flexible enough to handle different types of input data? From 593c2f0ca128a86c82bbfc9f4b734f48fc20fd32 Mon Sep 17 00:00:00 2001 From: Wolfgang Maier Date: Thu, 26 Sep 2024 16:35:17 +0200 Subject: [PATCH 10/13] Point to updated data library folder --- .../tutorials/sars-cov-2-variant-discovery/tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md b/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md index e0dbc1ef54b58f..c95849077f4a38 100644 --- a/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md +++ b/topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md @@ -241,7 +241,7 @@ For the suggested batch of early Omicron data we suggest downloading it via URLs > > - Option 2: Import from a shared data library > -> {% snippet faqs/galaxy/datasets_import_from_data_library.md astype="as a Collection" collection_type="List of Pairs" collection_name="Sequencing data" tohistory="the history you created for this tutorial" path="GTN - Material / Variant analysis / Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data / DOI: 10.5281/zenodo.5036686" box_type="none" %} +> {% snippet faqs/galaxy/datasets_import_from_data_library.md astype="as a Collection" collection_type="List of Pairs" collection_name="Sequencing data" tohistory="the history you created for this tutorial" path="GTN - Material / Variant analysis / Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data / Omicron_batch_analysis" box_type="none" %} > {: .hands_on} From f4044d5cf0b2881d7b271c041fe30f35453afe82 Mon Sep 17 00:00:00 2001 From: martenson Date: Sun, 29 Sep 2024 23:29:55 +0000 Subject: [PATCH 11/13] Compress Images --- .../img/workflow-entry.png | Bin 13843 -> 9495 bytes .../img/workflow-invocation.png | Bin 34524 -> 24548 bytes .../img/workflow-run-page.png | Bin 23968 -> 16492 bytes 3 files 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metadata/git-mod-efc7be5ba874506b92c304fa69236167ebd2e82a.txt rename to metadata/git-mod-d14fd5ed9616d1957ef6f84225762d6b467e69e7.txt index 8636a30910025f..4b43764b27e425 100644 --- a/metadata/git-mod-efc7be5ba874506b92c304fa69236167ebd2e82a.txt +++ b/metadata/git-mod-d14fd5ed9616d1957ef6f84225762d6b467e69e7.txt @@ -1,3 +1,154 @@ +GTN_GTN:1727436959 + +topics/genome-annotation/tutorials/amr-gene-detection/tutorial.md +GTN_GTN:1727434118 + +Gemfile.lock +GTN_GTN:1727434087 + +topics/assembly/tutorials/vgp_genome_assembly/tutorial.md +topics/community/tutorials/sig_define/tutorial.md +topics/dev/tutorials/community-tool-table/tutorial.md +topics/dev/tutorials/tool-annotation/tutorial.md +topics/dev/tutorials/tool-from-scratch/tutorial.md +topics/dev/tutorials/tool-generators-advanced/tutorial.md +topics/fair/tutorials/fair-data-registration/tutorial.md +topics/fair/tutorials/ro-crate-galaxy-best-practices/tutorial.md +topics/genome-annotation/tutorials/secondary-metabolite-discovery/tutorial.md +topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md +topics/single-cell/tutorials/GO-enrichment/tutorial.md +topics/single-cell/tutorials/scrna-case_alevin-combine-datasets/tutorial.md +topics/transcriptomics/tutorials/differential-isoform-expression/tutorial.md +topics/variant-analysis/tutorials/beacon_cnv_query/tutorial.md +topics/variant-analysis/tutorials/beaconise_1000hg/tutorial.md +GTN_GTN:1727366404 + +topics/variant-analysis/tutorials/sars-cov-2-variant-discovery/tutorial.md +GTN_GTN:1727344222 + +_layouts/event.html +GTN_GTN:1727343522 + +.github/workflows/ci-main.yml +GTN_GTN:1727343258 + +_config.yml +assets/js/main.js +assets/js/tutorial-mode.js +GTN_GTN:1727342401 + +topics/data-science/tutorials/sql-advanced/tutorial.md +GTN_GTN:1727339855 + +_plugins/jekyll-jsonld.rb +GTN_GTN:1727337973 + +_config.yml +assets/js/main.js +assets/js/tutorial-mode.js +GTN_GTN:1727337768 + +_config.yml +faqs/galaxy/workflows_best_practices.md +topics/fair/tutorials/ro-crate-galaxy-best-practices/img/workflow-entry.png +topics/fair/tutorials/ro-crate-galaxy-best-practices/img/workflow-invocation.png +topics/fair/tutorials/ro-crate-galaxy-best-practices/img/workflow-run-page.png +topics/fair/tutorials/ro-crate-galaxy-best-practices/tutorial.md +topics/fair/tutorials/ro-crate-submitting-life-monitor/tutorial.md +GTN_GTN:1727337201 + +topics/assembly/tutorials/assembly-decontamination/tutorial.md +GTN_GTN:1727336779 + +topics/microbiome/tutorials/dada-16S/tutorial.md +GTN_GTN:1727335798 + +topics/assembly/tutorials/mitochondrion-assembly/tutorial.md +GTN_GTN:1727277279 + +_plugins/jekyll-jsonld.rb +_plugins/util.rb +GTN_GTN:1727255537 + +_layouts/event-track.html +events/galaxy-academy-2024.md +events/tracks/gta2024-assembly.md +events/tracks/gta2024-bacterial-genomics.md +events/tracks/gta2024-bycovid.md +events/tracks/gta2024-microbiome.md +events/tracks/gta2024-ml.md +events/tracks/gta2024-proteomics.md +events/tracks/gta2024-single-cell.md +events/tracks/gta2024-transcriptomics.md +GTN_GTN:1727255502 + +bin/lint.rb +GTN_GTN:1727253183 + +bin/news.rb +GTN_GTN:1727250881 + +topics/admin/tutorials/interactive-tools/slides.html +topics/admin/tutorials/interactive-tools/tutorial.md +GTN_GTN:1727189728 + +topics/microbiome/tutorials/diversity/tutorial.md +GTN_GTN:1727129913 + +topics/single-cell/tutorials/scrna-scanpy-pbmc3k/tutorial.md +GTN_GTN:1727102130 + +metadata/workflowhub.yml +GTN_GTN:1727090456 + +_includes/instance-dropdown.html +_layouts/topic.html +GTN_GTN:1727076651 + +topics/ecology/tutorials/Ecoregionalization_tutorial/Images/2_example.png +topics/ecology/tutorials/Ecoregionalization_tutorial/Images/BRT-Echinodermata_Crinoidea_Comatulida_Antedonidae_Florometra_mawsoni__pred_plot.png +topics/ecology/tutorials/Ecoregionalization_tutorial/Images/JLN_param_example.png +topics/ecology/tutorials/Ecoregionalization_tutorial/Images/Map.png +topics/ecology/tutorials/Ecoregionalization_tutorial/Images/NA_example.png +topics/ecology/tutorials/Ecoregionalization_tutorial/Images/advanced_out_example.png +topics/ecology/tutorials/Ecoregionalization_tutorial/Images/pivot_file_example.png +topics/single-cell/images/GO-enrichment/slides_images/components_5.png +topics/single-cell/images/GO-enrichment/slides_images/enrichment_7.png +topics/single-cell/images/GO-enrichment/slides_images/example1_16.png +topics/single-cell/images/GO-enrichment/slides_images/example2.png +topics/single-cell/images/GO-enrichment/slides_images/example2_int.png +topics/single-cell/images/GO-enrichment/slides_images/example_6.png +topics/single-cell/images/GO-enrichment/slides_images/go_3.png +topics/single-cell/images/GO-enrichment/slides_images/go_enrichment_8.png +topics/single-cell/images/GO-enrichment/slides_images/hierarchy_4.png 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+topics/single-cell/images/scrna-scanpy-pbmc3k/umap_after_clustering.png +topics/single-cell/images/scrna-scanpy-pbmc3k/umap_annotated_clusters.png +topics/single-cell/images/scrna-scanpy-pbmc3k/umap_before_clustering.png +topics/single-cell/images/scrna-scanpy-pbmc3k/umap_plot_marker_genes.png +topics/single-cell/images/scrna-scanpy-pbmc3k/violin_plot_marker_genes.png +topics/single-cell/images/scrna-scanpy-pbmc3k/violin_plot_rank_genes_groups_CST3_NKG7_PPBP.png +topics/single-cell/images/workflow.png +GTN_GTN:1727076602 + +metadata/git-mod-efc7be5ba874506b92c304fa69236167ebd2e82a.txt +metadata/git-pub-efc7be5ba874506b92c304fa69236167ebd2e82a.txt +GTN_GTN:1727076570 + +metadata/shortlinks.yaml GTN_GTN:1727009190 topics/introduction/tutorials/galaxy-intro-101/tutorial.md diff --git a/metadata/git-pub-efc7be5ba874506b92c304fa69236167ebd2e82a.txt b/metadata/git-pub-d14fd5ed9616d1957ef6f84225762d6b467e69e7.txt similarity index 99% rename from metadata/git-pub-efc7be5ba874506b92c304fa69236167ebd2e82a.txt rename to metadata/git-pub-d14fd5ed9616d1957ef6f84225762d6b467e69e7.txt index e9dd4613da2a2c..ce0e8077daf8a9 100644 --- a/metadata/git-pub-efc7be5ba874506b92c304fa69236167ebd2e82a.txt +++ b/metadata/git-pub-d14fd5ed9616d1957ef6f84225762d6b467e69e7.txt @@ -1,3 +1,10 @@ +GTN_GTN:1727337973 + +A assets/js/tutorial-mode.js +GTN_GTN:1727076602 + +R099 metadata/git-mod-b5acaf862a6ef65d9660d4ea2d6152029e21f078.txt metadata/git-mod-efc7be5ba874506b92c304fa69236167ebd2e82a.txt +R099 metadata/git-pub-b5acaf862a6ef65d9660d4ea2d6152029e21f078.txt metadata/git-pub-efc7be5ba874506b92c304fa69236167ebd2e82a.txt GTN_GTN:1726674476 A topics/single-cell/faqs/gtn-in-galaxy_mode-cs.md From 6e41c84ce998e3676f56ce47c2baac2478a9073f Mon Sep 17 00:00:00 2001 From: Tom Harrop Date: Mon, 30 Sep 2024 15:39:02 +1000 Subject: [PATCH 13/13] fix typo --- topics/proteomics/tutorials/encyclopedia/tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/topics/proteomics/tutorials/encyclopedia/tutorial.md b/topics/proteomics/tutorials/encyclopedia/tutorial.md index c2414058e75b5b..04dfc2a7e96e37 100644 --- a/topics/proteomics/tutorials/encyclopedia/tutorial.md +++ b/topics/proteomics/tutorials/encyclopedia/tutorial.md @@ -102,7 +102,7 @@ In a typical DIA-MS experiment, the precursor scan usually ranges between 400-10 > https://zenodo.org/records/13505774/files/191023JAT06_P_1ug_595_705_4_20.raw > https://zenodo.org/records/13505774/files/191023JAT07_P_1ug_695_805_4_20.raw > https://zenodo.org/records/13505774/files/191023JAT08_P_1ug_795_905_4_20.raw -> ttps://zenodo.org/records/13505774/files/191023JAT09_P_1ug_895_1005_4_20.raw +> https://zenodo.org/records/13505774/files/191023JAT09_P_1ug_895_1005_4_20.raw > https://zenodo.org/record/4926594/files/T4_Salmonella_Ecoli_Bacillus_BS_191102.fasta > https://zenodo.org/record/4926594/files/T4_Salmonella_Ecoli_Bacillus_fasta_trypsin_z2_nce33_BS_191102.dlib > ```