DEG Part - Ref Based RNA Seq - Transcriptomics - GTN

Run Workflow in Galaxy

• Galaxy Australia
• Galaxy Europe
• Galaxy France
• Galaxy Main
• Import to another server (≥23.0+ only!)

flowchart TD
  0["ℹ️ Input Collection\nInput Dataset Collection"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nDrosophila_melanogaster.BDGP6.32.109_UCSC.gtf.gz"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\nheader"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["ℹ️ Input Dataset\nKEGG pathways to plot"];
  style 3 stroke:#2c3143,stroke-width:4px;
  4["Extract samples’ name"];
  0 -->|output| 4;
  5["Compute gene length"];
  1 -->|output| 5;
  6["Extract groups"];
  4 -->|output| 6;
  7["Change Case"];
  5 -->|length| 7;
  8["Tag elements with groups"];
  0 -->|output| 8;
  6 -->|outfile| 8;
  9["Differential Analysis"];
  8 -->|output| 9;
  c1ff3e9a-46d3-4862-adb6-076ea951be26["Output\nDESeq2_plots"];
  9 --> c1ff3e9a-46d3-4862-adb6-076ea951be26;
  style c1ff3e9a-46d3-4862-adb6-076ea951be26 stroke:#2c3143,stroke-width:4px;
  b430e84e-cfa5-48e8-92a7-ef5630ced1e5["Output\nDESeq2_normalized_counts"];
  9 --> b430e84e-cfa5-48e8-92a7-ef5630ced1e5;
  style b430e84e-cfa5-48e8-92a7-ef5630ced1e5 stroke:#2c3143,stroke-width:4px;
  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;
  style ae762394-0e90-4b9a-a7b4-7cffeccc80a7 stroke:#2c3143,stroke-width:4px;
  23["Filter"];
  18 -->|wallenius_tab| 23;
  b788d5b7-119c-418a-a12b-a97ef7ea5bf2["Output\ngo_overrepresented"];
  23 --> b788d5b7-119c-418a-a12b-a97ef7ea5bf2;
  style b788d5b7-119c-418a-a12b-a97ef7ea5bf2 stroke:#2c3143,stroke-width:4px;
  24["Filter"];
  19 -->|wallenius_tab| 24;
  69f80c89-fc7d-4bea-836f-34e68615abcd["Output\nkegg_underrepresented"];
  24 --> 69f80c89-fc7d-4bea-836f-34e68615abcd;
  style 69f80c89-fc7d-4bea-836f-34e68615abcd stroke:#2c3143,stroke-width:4px;
  25["Filter"];
  19 -->|wallenius_tab| 25;
  930f1461-0ade-4744-a83d-843108c4b597["Output\nkegg_overrepresented"];
  25 --> 930f1461-0ade-4744-a83d-843108c4b597;
  style 930f1461-0ade-4744-a83d-843108c4b597 stroke:#2c3143,stroke-width:4px;
  26["Pathview"];
  20 -->|out_file1| 26;
  3 -->|output| 26;
  7cdd4475-6de3-4c02-be8d-d76e788980f6["Output\npathview_plot"];
  26 --> 7cdd4475-6de3-4c02-be8d-d76e788980f6;
  style 7cdd4475-6de3-4c02-be8d-d76e788980f6 stroke:#2c3143,stroke-width:4px;
  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;

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

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:

Version History

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