DEG Part - Ref Based RNA Seq - Transcriptomics - GTN
transcriptomics-ref-based/deg-analysis
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10["Compute"]; 9 -->|deseq_out| 10; 11["Annotate DESeq2/DEXSeq output tables"]; 1 -->|output| 11; 9 -->|deseq_out| 11; 12["Table Compute"]; 9 -->|counts_out| 12; 13["Cut"]; 10 -->|out_file1| 13; 14["Concatenate datasets"]; 2 -->|output| 14; 11 -->|output| 14; 11f46837-7dbb-453b-962a-3c97cb0faad4["Output\nDESeq2_annotated_results_with_header"]; 14 --> 11f46837-7dbb-453b-962a-3c97cb0faad4; style 11f46837-7dbb-453b-962a-3c97cb0faad4 stroke:#2c3143,stroke-width:4px; 15["Table Compute"]; 9 -->|counts_out| 15; 12 -->|table| 15; 32004d23-7c99-4405-a65f-fd861b40c949["Output\nz_score"]; 15 --> 32004d23-7c99-4405-a65f-fd861b40c949; style 32004d23-7c99-4405-a65f-fd861b40c949 stroke:#2c3143,stroke-width:4px; 16["Change Case"]; 13 -->|out_file1| 16; 17["Filter"]; 14 -->|out_file1| 17; 18["goseq"]; 16 -->|out_file1| 18; 7 -->|out_file1| 18; a0dd7397-7262-4336-abd6-a915ab6be36a["Output\ngo_genes"]; 18 --> a0dd7397-7262-4336-abd6-a915ab6be36a; style a0dd7397-7262-4336-abd6-a915ab6be36a stroke:#2c3143,stroke-width:4px; 659fec58-4ed5-4aee-9e50-7acce21113cb["Output\ngo_plot"]; 18 --> 659fec58-4ed5-4aee-9e50-7acce21113cb; style 659fec58-4ed5-4aee-9e50-7acce21113cb stroke:#2c3143,stroke-width:4px; c06c58d4-ab5d-49da-b481-baf668c6fc29["Output\ngo_terms"]; 18 --> c06c58d4-ab5d-49da-b481-baf668c6fc29; style c06c58d4-ab5d-49da-b481-baf668c6fc29 stroke:#2c3143,stroke-width:4px; 19["goseq"]; 16 -->|out_file1| 19; 7 -->|out_file1| 19; 9872b017-9b39-4cd3-b232-a305979a782b["Output\nkegg_genes"]; 19 --> 9872b017-9b39-4cd3-b232-a305979a782b; style 9872b017-9b39-4cd3-b232-a305979a782b stroke:#2c3143,stroke-width:4px; 8d0ac5be-ac7d-4f10-85ac-d3461f561a50["Output\nkegg_pathways"]; 19 --> 8d0ac5be-ac7d-4f10-85ac-d3461f561a50; style 8d0ac5be-ac7d-4f10-85ac-d3461f561a50 stroke:#2c3143,stroke-width:4px; 20["Cut"]; 17 -->|out_file1| 20; 21["Filter"]; 17 -->|out_file1| 21; 22["Filter"]; 18 -->|wallenius_tab| 22; ae762394-0e90-4b9a-a7b4-7cffeccc80a7["Output\ngo_underrepresented"]; 22 --> ae762394-0e90-4b9a-a7b4-7cffeccc80a7; 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27["Join two Datasets"]; 9 -->|counts_out| 27; 21 -->|out_file1| 27; 28["Group"]; 22 -->|out_file1| 28; d1ae921d-2e2b-46d8-95a2-4443f5a1b3b4["Output\ngo_underrepresented_categories"]; 28 --> d1ae921d-2e2b-46d8-95a2-4443f5a1b3b4; style d1ae921d-2e2b-46d8-95a2-4443f5a1b3b4 stroke:#2c3143,stroke-width:4px; 29["Group"]; 23 -->|out_file1| 29; 4d2d01eb-15d2-4863-a522-9462c15eb51c["Output\ngo_overrepresented_categories"]; 29 --> 4d2d01eb-15d2-4863-a522-9462c15eb51c; style 4d2d01eb-15d2-4863-a522-9462c15eb51c stroke:#2c3143,stroke-width:4px; 30["Cut"]; 27 -->|out_file1| 30; 31["heatmap2"]; 30 -->|out_file1| 31; 42cb6b68-4ed6-4b6e-9312-744b9e0c1442["Output\nheatmap_log"]; 31 --> 42cb6b68-4ed6-4b6e-9312-744b9e0c1442; style 42cb6b68-4ed6-4b6e-9312-744b9e0c1442 stroke:#2c3143,stroke-width:4px; 32["heatmap2"]; 30 -->|out_file1| 32; 0ecef5aa-76ed-4fe7-9244-3b32d231e7f3["Output\nheatmap_zscore"]; 32 --> 0ecef5aa-76ed-4fe7-9244-3b32d231e7f3; style 0ecef5aa-76ed-4fe7-9244-3b32d231e7f3 stroke:#2c3143,stroke-width:4px;
Inputs
Input | Label |
---|---|
Input dataset collection | Input Dataset Collection |
Input dataset | Drosophila_melanogaster.BDGP6.32.109_UCSC.gtf.gz |
Input dataset | header |
Input dataset | KEGG pathways to plot |
Outputs
From | Output | Label |
---|---|---|
toolshed.g2.bx.psu.edu/repos/iuc/deseq2/deseq2/2.11.40.8+galaxy0 | DESeq2 | Differential Analysis |
toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1 | Concatenate datasets | |
toolshed.g2.bx.psu.edu/repos/iuc/table_compute/table_compute/1.2.4+galaxy0 | Table Compute | |
toolshed.g2.bx.psu.edu/repos/iuc/goseq/goseq/1.50.0+galaxy0 | goseq | |
toolshed.g2.bx.psu.edu/repos/iuc/goseq/goseq/1.50.0+galaxy0 | goseq | |
Filter1 | Filter | |
Filter1 | Filter | |
Filter1 | Filter | |
Filter1 | Filter | |
toolshed.g2.bx.psu.edu/repos/iuc/pathview/pathview/1.34.0+galaxy0 | Pathview | |
Grouping1 | Group | |
Grouping1 | Group | |
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_heatmap2/ggplot2_heatmap2/3.1.3.1+galaxy0 | heatmap2 | |
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_heatmap2/ggplot2_heatmap2/3.1.3.1+galaxy0 | heatmap2 |
Tools
To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.
Importing into Galaxy
Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!Hands-on: Importing a workflow
- Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
- Click on galaxy-upload Import at the top-right of the screen
- Provide your workflow
- Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
- Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
- Click the Import workflow button
Below is a short video demonstrating how to import a workflow from GitHub using this procedure:
Video: Importing a workflow from URL
Version History
Version | Commit | Time | Comments |
---|---|---|---|
24 | a1251f286 | 2024-07-05 09:38:54 | Removed 'comments' tags |
23 | 7d1cc771a | 2024-07-05 09:15:02 | Updated tools in 'DEG Part' workflow |
22 | 41dead43e | 2023-05-02 10:31:07 | add mo orcid to workflows |
21 | 36eb5cf82 | 2023-04-28 17:26:00 | update workflows and tests |
20 | bba94e019 | 2023-04-25 09:47:41 | fix workflow of DEG |
19 | 639885e9c | 2023-04-25 08:06:12 | fix deseq2 params |
18 | 0e8a4c42b | 2023-04-25 07:58:48 | fix input label in workflow deg |
17 | 8fc9c9026 | 2023-04-25 07:46:15 | add creators and licence to workflows |
16 | e9ac61d9e | 2023-04-25 07:32:39 | update deg-analysis workflow |
15 | 543df91d6 | 2023-01-11 16:53:40 | Update Compute tool to latest version |
14 | 47113bebd | 2022-06-30 15:22:32 | Fix additional error |
13 | f5e192fc7 | 2022-06-30 14:29:26 | Fix workflow |
12 | 815b50713 | 2022-04-15 15:14:47 | fix header parameter in deseq2 workflow |
11 | d377962b2 | 2022-04-14 22:18:06 | update workflow |
10 | 19e4e0680 | 2022-04-14 12:29:01 | update DEG wf and test |
9 | d3beb91a7 | 2022-04-14 08:30:39 | update deg-analysis workflow and test |
8 | a6e8658a7 | 2022-04-13 16:01:54 | update workflow for part2 |
7 | e08c38b2b | 2022-04-05 19:36:51 | add tag |
6 | e675ce786 | 2022-04-05 13:27:17 | small updates |
5 | 35d565217 | 2022-04-05 13:18:22 | update workflows |
4 | 05462ddf4 | 2022-04-05 11:54:45 | update workflow |
3 | 667ff3de9 | 2020-01-22 10:59:29 | annotation |
2 | eb4d724e0 | 2020-01-15 10:41:35 | Workflow renaming |
1 | e477f2b7f | 2019-09-10 09:22:59 | Split workflow and add more tests |
For Admins
Installing the workflow tools
wget https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/ref-based/workflows/deg-analysis.ga -O workflow.ga workflow-to-tools -w workflow.ga -o tools.yaml shed-tools install -g GALAXY -a API_KEY -t tools.yaml workflow-install -g GALAXY -a API_KEY -w workflow.ga --publish-workflows