QC + Mapping + Counting - Ref Based RNA Seq - Transcriptomics - GTN - subworkflows

Run Workflow in Galaxy

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

flowchart TD
  0["ℹ️ Input Collection\nPaired list collection with PE fastqs"];
  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["🛠️ Subworkflow\nFastQC"];
  style 2 fill:#edd,stroke:#900,stroke-width:4px;
  0 -->|output| 2;
  5f7652f1-e225-4ad1-8dbd-4d21544edb89["Output\nmultiqc_fastqc_html"];
  2 --> 5f7652f1-e225-4ad1-8dbd-4d21544edb89;
  style 5f7652f1-e225-4ad1-8dbd-4d21544edb89 stroke:#2c3143,stroke-width:4px;
  3["🛠️ Subworkflow\ncutadapt"];
  style 3 fill:#edd,stroke:#900,stroke-width:4px;
  0 -->|output| 3;
  41c7fbb5-655b-457c-8ba7-0e2eeab3d7ee["Output\nmultiqc_cutadapt_html"];
  3 --> 41c7fbb5-655b-457c-8ba7-0e2eeab3d7ee;
  style 41c7fbb5-655b-457c-8ba7-0e2eeab3d7ee stroke:#2c3143,stroke-width:4px;
  4["🛠️ Subworkflow\nSTAR + multiQC"];
  style 4 fill:#edd,stroke:#900,stroke-width:4px;
  1 -->|output| 4;
  3 -->|out_pairs| 4;
  8aa5ef30-3f09-4a93-944d-0d89101c056a["Output\nmultiqc_star_html"];
  4 --> 8aa5ef30-3f09-4a93-944d-0d89101c056a;
  style 8aa5ef30-3f09-4a93-944d-0d89101c056a stroke:#2c3143,stroke-width:4px;
  11af5c57-91b4-496c-9b0c-b02904963f81["Output\nSTAR_BAM"];
  4 --> 11af5c57-91b4-496c-9b0c-b02904963f81;
  style 11af5c57-91b4-496c-9b0c-b02904963f81 stroke:#2c3143,stroke-width:4px;
  5["🛠️ Subworkflow\nmore QC"];
  style 5 fill:#edd,stroke:#900,stroke-width:4px;
  1 -->|output| 5;
  4 -->|STAR_BAM| 5;
  f2eed352-ca21-4d65-8810-f5a1d3c282b4["Output\nmultiqc_read_distrib_html"];
  5 --> f2eed352-ca21-4d65-8810-f5a1d3c282b4;
  style f2eed352-ca21-4d65-8810-f5a1d3c282b4 stroke:#2c3143,stroke-width:4px;
  b306cb12-a275-4c6d-b609-47fdc208864b["Output\nmultiqc_reads_per_chrom_html"];
  5 --> b306cb12-a275-4c6d-b609-47fdc208864b;
  style b306cb12-a275-4c6d-b609-47fdc208864b stroke:#2c3143,stroke-width:4px;
  3375d63c-cdc3-4fbb-8a55-6f504c934918["Output\nmultiqc_gene_body_cov_html"];
  5 --> 3375d63c-cdc3-4fbb-8a55-6f504c934918;
  style 3375d63c-cdc3-4fbb-8a55-6f504c934918 stroke:#2c3143,stroke-width:4px;
  3ea82568-5698-49a7-88fe-91381070aac2["Output\nmultiqc_dup_html"];
  5 --> 3ea82568-5698-49a7-88fe-91381070aac2;
  style 3ea82568-5698-49a7-88fe-91381070aac2 stroke:#2c3143,stroke-width:4px;
  6["🛠️ Subworkflow\nDetermine strandness"];
  style 6 fill:#edd,stroke:#900,stroke-width:4px;
  4 -->|STAR_BAM| 6;
  1 -->|output| 6;
  4 -->|signal_unique_str1| 6;
  4 -->|signal_unique_str2| 6;
  4 -->|reads_per_gene| 6;
  fb810859-f2d0-43f8-ac7c-5c714c5c6805["Output\ninferexperiment"];
  6 --> fb810859-f2d0-43f8-ac7c-5c714c5c6805;
  style fb810859-f2d0-43f8-ac7c-5c714c5c6805 stroke:#2c3143,stroke-width:4px;
  9727824a-3eb2-4430-92d1-b3c40c3041d1["Output\npgt"];
  6 --> 9727824a-3eb2-4430-92d1-b3c40c3041d1;
  style 9727824a-3eb2-4430-92d1-b3c40c3041d1 stroke:#2c3143,stroke-width:4px;
  105313d8-e31a-405d-8fcd-cc5fd93275e2["Output\nmultiqc_star_counts_html"];
  6 --> 105313d8-e31a-405d-8fcd-cc5fd93275e2;
  style 105313d8-e31a-405d-8fcd-cc5fd93275e2 stroke:#2c3143,stroke-width:4px;
  7["🛠️ Subworkflow\ncount STAR"];
  style 7 fill:#edd,stroke:#900,stroke-width:4px;
  1 -->|output| 7;
  4 -->|reads_per_gene| 7;
  5fee8aff-4023-43f1-a653-f5af5357d798["Output\ncounts_from_star"];
  7 --> 5fee8aff-4023-43f1-a653-f5af5357d798;
  style 5fee8aff-4023-43f1-a653-f5af5357d798 stroke:#2c3143,stroke-width:4px;
  bd3388e6-5b45-4fdc-9780-3efd1c34ebf8["Output\ncounts_from_star_sorted"];
  7 --> bd3388e6-5b45-4fdc-9780-3efd1c34ebf8;
  style bd3388e6-5b45-4fdc-9780-3efd1c34ebf8 stroke:#2c3143,stroke-width:4px;
  7b7c698b-4808-4b45-adf1-686f8d273d18["Output\nGene length"];
  7 --> 7b7c698b-4808-4b45-adf1-686f8d273d18;
  style 7b7c698b-4808-4b45-adf1-686f8d273d18 stroke:#2c3143,stroke-width:4px;
  8["🛠️ Subworkflow\ncount featureCount"];
  style 8 fill:#edd,stroke:#900,stroke-width:4px;
  1 -->|output| 8;
  4 -->|STAR_BAM| 8;
  f0de4714-4df8-4506-90d9-384537ad663e["Output\nfeatureCounts_sorted"];
  8 --> f0de4714-4df8-4506-90d9-384537ad663e;
  style f0de4714-4df8-4506-90d9-384537ad663e stroke:#2c3143,stroke-width:4px;
  8b9d6c76-6e82-4691-b8bc-9996d6ae1594["Output\nfeatureCounts_gene_length"];
  8 --> 8b9d6c76-6e82-4691-b8bc-9996d6ae1594;
  style 8b9d6c76-6e82-4691-b8bc-9996d6ae1594 stroke:#2c3143,stroke-width:4px;
  152ba01e-d4f2-4227-8812-87648a1c19ea["Output\nmultiqc_featureCounts_html"];
  8 --> 152ba01e-d4f2-4227-8812-87648a1c19ea;
  style 152ba01e-d4f2-4227-8812-87648a1c19ea stroke:#2c3143,stroke-width:4px;
  46c7a2e8-7819-4715-a028-7ad1de9ed605["Output\nfeatureCounts"];
  8 --> 46c7a2e8-7819-4715-a028-7ad1de9ed605;
  style 46c7a2e8-7819-4715-a028-7ad1de9ed605 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/qc-mapping-counting.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