Workflows

These workflows are associated with Metatranscriptomics analysis using microbiome RNA-seq data (short)

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.

flowchart TD
  0["ℹ️ Input Dataset\nT1A_forward"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nT1A_reverse"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["Quality control Forward"];
  0 -->|output| 2;
  025f2766-0802-461e-afbd-a716e6f81ba8["Output\nFastQC on input dataset(s): RawData"];
  2 --> 025f2766-0802-461e-afbd-a716e6f81ba8;
  style 025f2766-0802-461e-afbd-a716e6f81ba8 stroke:#2c3143,stroke-width:4px;
  a54ee2fd-7bce-439a-9f1f-f9ec9bf00efd["Output\nFastQC on input dataset(s): Webpage"];
  2 --> a54ee2fd-7bce-439a-9f1f-f9ec9bf00efd;
  style a54ee2fd-7bce-439a-9f1f-f9ec9bf00efd stroke:#2c3143,stroke-width:4px;
  3["Quality control Reverse"];
  1 -->|output| 3;
  4["Cutadapt"];
  0 -->|output| 4;
  1 -->|output| 4;
  4bc7c8a4-b985-41dd-b67f-a3dfecd38a67["Output\nCutadapt on input dataset(s): Read 1 Output"];
  4 --> 4bc7c8a4-b985-41dd-b67f-a3dfecd38a67;
  style 4bc7c8a4-b985-41dd-b67f-a3dfecd38a67 stroke:#2c3143,stroke-width:4px;
  36ec0bba-e49a-47e2-b916-afec9b35cc3e["Output\nCutadapt on input dataset(s): Read 2 Output"];
  4 --> 36ec0bba-e49a-47e2-b916-afec9b35cc3e;
  style 36ec0bba-e49a-47e2-b916-afec9b35cc3e stroke:#2c3143,stroke-width:4px;
  5["MultiQC"];
  2 -->|text_file| 5;
  3 -->|text_file| 5;
  b9ca2123-0ee0-40a0-b2ec-cfc94fa35849["Output\nMultiQC on input dataset(s): Stats"];
  5 --> b9ca2123-0ee0-40a0-b2ec-cfc94fa35849;
  style b9ca2123-0ee0-40a0-b2ec-cfc94fa35849 stroke:#2c3143,stroke-width:4px;
  e94ceb7a-0d6b-41c8-b79d-035b315e0a06["Output\nMultiQC on input dataset(s): Webpage"];
  5 --> e94ceb7a-0d6b-41c8-b79d-035b315e0a06;
  style e94ceb7a-0d6b-41c8-b79d-035b315e0a06 stroke:#2c3143,stroke-width:4px;
  6["rRNA/rDNA selection"];
  4 -->|out1| 6;
  4 -->|out2| 6;
  7["FASTQ interlacer"];
  6 -->|unaligned_forward| 7;
  6 -->|unaligned_reverse| 7;
  b060eebc-cd14-486e-806e-aae983bdf52d["Output\nFASTQ interlacer singles from input dataset(s)"];
  7 --> b060eebc-cd14-486e-806e-aae983bdf52d;
  style b060eebc-cd14-486e-806e-aae983bdf52d stroke:#2c3143,stroke-width:4px;
  70b738db-5451-4eaa-91c0-eb445be297fb["Output\nFASTQ interlacer pairs from input dataset(s)"];
  7 --> 70b738db-5451-4eaa-91c0-eb445be297fb;
  style 70b738db-5451-4eaa-91c0-eb445be297fb stroke:#2c3143,stroke-width:4px;
	

flowchart TD
  0["ℹ️ Input Dataset\nQC controlled forward reads"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nQC controlled reverse reads"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["Taxonomic assignation"];
  0 -->|output| 2;
  1 -->|output| 2;
  b3e3198d-394e-4aeb-ba6c-9e73bfe8d049["Output\nMetaPhlAn on input dataset(s): SAM file"];
  2 --> b3e3198d-394e-4aeb-ba6c-9e73bfe8d049;
  style b3e3198d-394e-4aeb-ba6c-9e73bfe8d049 stroke:#2c3143,stroke-width:4px;
  a4ecdc94-d012-413f-a9cb-6f3e9ee70d5b["Output\nMetaPhlAn on input dataset(s): Predicted taxon relative abundances"];
  2 --> a4ecdc94-d012-413f-a9cb-6f3e9ee70d5b;
  style a4ecdc94-d012-413f-a9cb-6f3e9ee70d5b stroke:#2c3143,stroke-width:4px;
  30a9e692-8d31-45bd-9246-81ddead3ba03["Output\nMetaPhlAn on input dataset(s): Bowtie2 output"];
  2 --> 30a9e692-8d31-45bd-9246-81ddead3ba03;
  style 30a9e692-8d31-45bd-9246-81ddead3ba03 stroke:#2c3143,stroke-width:4px;
  2465a9ab-a28e-4c58-b647-b6792f77ddf2["Output\nMetaPhlAn on input dataset(s): BIOM file"];
  2 --> 2465a9ab-a28e-4c58-b647-b6792f77ddf2;
  style 2465a9ab-a28e-4c58-b647-b6792f77ddf2 stroke:#2c3143,stroke-width:4px;
  3["Cut"];
  2 -->|output_file| 3;
  4["Krona pie chart"];
  2 -->|krona_output_file| 4;
  5["Export to GraPhlAn"];
  3 -->|out_file1| 5;
  f578de2e-6edd-4ee0-9bc4-9371d6fd957f["Output\nExport to GraPhlAn on input dataset(s): Annotation"];
  5 --> f578de2e-6edd-4ee0-9bc4-9371d6fd957f;
  style f578de2e-6edd-4ee0-9bc4-9371d6fd957f stroke:#2c3143,stroke-width:4px;
  4e9cfae0-ee7b-4347-84db-5a3e24688e50["Output\nExport to GraPhlAn on input dataset(s): Tree"];
  5 --> 4e9cfae0-ee7b-4347-84db-5a3e24688e50;
  style 4e9cfae0-ee7b-4347-84db-5a3e24688e50 stroke:#2c3143,stroke-width:4px;
  6["Generation, personalization and annotation of tree"];
  5 -->|annotation| 6;
  5 -->|tree| 6;
  edf4ecaf-dddd-43a3-ba4a-d683671c1815["Output\nGeneration, personalization and annotation of tree on input dataset(s): Tree in PhyloXML"];
  6 --> edf4ecaf-dddd-43a3-ba4a-d683671c1815;
  style edf4ecaf-dddd-43a3-ba4a-d683671c1815 stroke:#2c3143,stroke-width:4px;
  7["Visualisation GraPhlAn"];
  6 -->|output_tree| 7;
  b304fe87-de7e-48d2-8774-9c52d2395fa4["Output\nGraPhlAn on input dataset(s): PNG"];
  7 --> b304fe87-de7e-48d2-8774-9c52d2395fa4;
  style b304fe87-de7e-48d2-8774-9c52d2395fa4 stroke:#2c3143,stroke-width:4px;
	

flowchart TD
  0["ℹ️ Input Dataset\nInterlaced non-rRNA reads"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nPredicted taxon relative abundances"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["Cut"];
  1 -->|output| 2;
  3["Metabolic assignation"];
  0 -->|output| 3;
  1 -->|output| 3;
  65797303-6f12-4ae8-9511-1af40f52e71d["Output\nHUMAnN on input dataset(s): Pathways and their abundance"];
  3 --> 65797303-6f12-4ae8-9511-1af40f52e71d;
  style 65797303-6f12-4ae8-9511-1af40f52e71d stroke:#2c3143,stroke-width:4px;
  5cae6935-448b-4af9-ad78-7b17490e4d4a["Output\nHUMAnN on input dataset(s): Pathways and their coverage"];
  3 --> 5cae6935-448b-4af9-ad78-7b17490e4d4a;
  style 5cae6935-448b-4af9-ad78-7b17490e4d4a stroke:#2c3143,stroke-width:4px;
  60492d72-7b3c-45c9-b32b-b6374ab08228["Output\nHUMAnN on input dataset(s): Log"];
  3 --> 60492d72-7b3c-45c9-b32b-b6374ab08228;
  style 60492d72-7b3c-45c9-b32b-b6374ab08228 stroke:#2c3143,stroke-width:4px;
  ba124b0f-cbd5-4b65-b87a-84cfa578a927["Output\nHUMAnN on input dataset(s): Gene families and their abundance"];
  3 --> ba124b0f-cbd5-4b65-b87a-84cfa578a927;
  style ba124b0f-cbd5-4b65-b87a-84cfa578a927 stroke:#2c3143,stroke-width:4px;
  4["Renormalize"];
  3 -->|gene_families_tsv| 4;
  5["Renormalize"];
  3 -->|pathabundance_tsv| 5;
  6["Regroup"];
  3 -->|gene_families_tsv| 6;
  7["Replace"];
  4 -->|output| 7;
  8["Unpack pathway abundances"];
  4 -->|output| 8;
  5 -->|output| 8;
  9["Rename features"];
  6 -->|output| 9;
  10["Split a HUMAnN table"];
  6 -->|output| 10;
  1ff60d0a-4a64-44c0-8b6f-bbdfa8566a0c["Output\nSplit a HUMAnN table on input dataset(s): Unstratified table"];
  10 --> 1ff60d0a-4a64-44c0-8b6f-bbdfa8566a0c;
  style 1ff60d0a-4a64-44c0-8b6f-bbdfa8566a0c stroke:#2c3143,stroke-width:4px;
  6a65ee93-3a2e-4a81-94ff-35917396bdfa["Output\nSplit a HUMAnN table on input dataset(s): Stratified table"];
  10 --> 6a65ee93-3a2e-4a81-94ff-35917396bdfa;
  style 6a65ee93-3a2e-4a81-94ff-35917396bdfa stroke:#2c3143,stroke-width:4px;
  11["Combination of taxonomic and metabolic assignations for gene families"];
  7 -->|outfile| 11;
  2 -->|out_file1| 11;
  b34cf972-ec0c-4ecc-ab77-bd0e61d8a0e2["Output\nCombine MetaPhlAn2 and HUMAnN2 outputs on input dataset(s): Gene family abundances related to genus/species abundances"];
  11 --> b34cf972-ec0c-4ecc-ab77-bd0e61d8a0e2;
  style b34cf972-ec0c-4ecc-ab77-bd0e61d8a0e2 stroke:#2c3143,stroke-width:4px;
  12["Select"];
  9 -->|output| 12;
  13["Select"];
  9 -->|output| 13;
  14["Select"];
  9 -->|output| 14;
	

flowchart TD
  0["ℹ️ Input Dataset\nPredicted taxon relative abundances"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nGene Family abundance"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\nPathway abundance"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["Cut"];
  0 -->|output| 3;
  4["Renormalize"];
  1 -->|output| 4;
  5["Regroup"];
  1 -->|output| 5;
  6["Renormalize"];
  2 -->|output| 6;
  7["Replace"];
  4 -->|output| 7;
  8["Rename features"];
  5 -->|output| 8;
  9["Split a HUMAnN table"];
  5 -->|output| 9;
  7aba96f3-1648-4126-8e58-ca10cbd2e46d["Output\nSplit a HUMAnN table on input dataset(s): Stratified table"];
  9 --> 7aba96f3-1648-4126-8e58-ca10cbd2e46d;
  style 7aba96f3-1648-4126-8e58-ca10cbd2e46d stroke:#2c3143,stroke-width:4px;
  2c36dc33-5981-4b2c-b615-a1677002e007["Output\nSplit a HUMAnN table on input dataset(s): Unstratified table"];
  9 --> 2c36dc33-5981-4b2c-b615-a1677002e007;
  style 2c36dc33-5981-4b2c-b615-a1677002e007 stroke:#2c3143,stroke-width:4px;
  10["Unpack pathway abundances"];
  4 -->|output| 10;
  6 -->|output| 10;
  11["Combination of taxonomic and metabolic assignations for gene families"];
  7 -->|outfile| 11;
  3 -->|out_file1| 11;
  46161015-b2db-4241-846e-27dd803b0fb3["Output\nCombine MetaPhlAn2 and HUMAnN2 outputs on input dataset(s): Gene family abundances related to genus/species abundances"];
  11 --> 46161015-b2db-4241-846e-27dd803b0fb3;
  style 46161015-b2db-4241-846e-27dd803b0fb3 stroke:#2c3143,stroke-width:4px;
  12["Select"];
  8 -->|output| 12;
  13["Select"];
  8 -->|output| 13;
  14["Select"];
  8 -->|output| 14;
	

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: