WF2_Discovery-Workflow
microbiome-clinical-mp-2-discovery/wf2-discovery-workflow
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flowchart TD 0["ℹ️ Input Dataset\nHuman UniProt Microbial Proteins from MetaNovo and cRAP "]; style 0 stroke:#2c3143,stroke-width:4px; 1["Identification Parameters: PAR file"]; 2["ℹ️ Input Collection\nRAW files Dataset Collection"]; style 2 stroke:#2c3143,stroke-width:4px; 3["Human SwissProt reviewed only"]; e0de9f90-a710-4b55-af62-41ba1c2d8e1f["Output\nHuman SwissProt (reviewed only)"]; 3 --> e0de9f90-a710-4b55-af62-41ba1c2d8e1f; style e0de9f90-a710-4b55-af62-41ba1c2d8e1f stroke:#2c3143,stroke-width:4px; 4["Contaminants cRAP"]; 5["ℹ️ Input Dataset\nExperimental Design Discovery MaxQuant"]; style 5 stroke:#2c3143,stroke-width:4px; 6["FastaCLI__MetaNovo_Human_SwissProt_cRAP_with_decoys_on_data_1_MetaNovo_Human_SwissProt_cRAP_concatenated_target_decoy.fasta"]; 0 -->|output| 6; 7["msconvert"]; 2 -->|output| 7; 8["Human SwissProt+cRAP"]; 3 -->|output_database| 8; 4 -->|output_database| 8; 2f14902f-b005-4c08-b6d1-6d7ee0b4b199["Output\nHuman SwissProt+cRAP"]; 8 --> 2f14902f-b005-4c08-b6d1-6d7ee0b4b199; style 2f14902f-b005-4c08-b6d1-6d7ee0b4b199 stroke:#2c3143,stroke-width:4px; 9["MaxQuant"]; 0 -->|output| 9; 2 -->|output| 9; 5 -->|output| 9; 10["Search GUI"]; 6 -->|input_database_concatenated_target_decoy| 10; 1 -->|Identification_Parameters_File| 10; 7 -->|output| 10; 11["FASTA-to-Tabular"]; 8 -->|output| 11; 12["Select microbial peptides MQ"]; 9 -->|peptides| 12; d7718bab-9e75-4729-bfb6-03bc3112a0e2["Output\nSelect microbial peptides (MQ)"]; 12 --> d7718bab-9e75-4729-bfb6-03bc3112a0e2; style d7718bab-9e75-4729-bfb6-03bc3112a0e2 stroke:#2c3143,stroke-width:4px; 13["Peptide Shaker"]; 10 -->|searchgui_results| 13; 14["Filter Tabular"]; 11 -->|output| 14; 15["MQ Peptide Sequences"]; 12 -->|out_file1| 15; 16["Select microbial peptides SGPS"]; 13 -->|output_peptides| 16; 14fd9080-df92-4c61-b1f1-3f700a166700["Output\nSelect microbial peptides (SGPS)"]; 16 --> 14fd9080-df92-4c61-b1f1-3f700a166700; style 14fd9080-df92-4c61-b1f1-3f700a166700 stroke:#2c3143,stroke-width:4px; 17["Select microbial PSMs"]; 13 -->|output_psm| 17; 18["Remove beginning"]; 15 -->|out_file1| 18; 19["Filter confident microbial peptides"]; 16 -->|out_file1| 19; 1c6c953f-d192-4953-938a-9f401315bc0d["Output\nFilter confident microbial peptides"]; 19 --> 1c6c953f-d192-4953-938a-9f401315bc0d; style 1c6c953f-d192-4953-938a-9f401315bc0d stroke:#2c3143,stroke-width:4px; 20["Filter confident microbial PSMs"]; 17 -->|out_file1| 20; d8ec7f0c-7ba1-4733-a3dc-74a9ef298dc2["Output\nFilter confident microbial PSMs"]; 20 --> d8ec7f0c-7ba1-4733-a3dc-74a9ef298dc2; style d8ec7f0c-7ba1-4733-a3dc-74a9ef298dc2 stroke:#2c3143,stroke-width:4px; 21["MQ Distinct Peptides"]; 18 -->|out_file1| 21; 07cae017-0b39-4065-b83e-b5f2e27fe740["Output\nMQ Peptides"]; 21 --> 07cae017-0b39-4065-b83e-b5f2e27fe740; style 07cae017-0b39-4065-b83e-b5f2e27fe740 stroke:#2c3143,stroke-width:4px; 22["Query Tabular"]; 20 -->|out_file1| 22; 20 -->|out_file1| 22; 14 -->|output| 22; 23["Cut"]; 22 -->|output| 23; 24["SGPS Distinct Peptides"]; 23 -->|out_file1| 24; b6c61697-ff52-43c0-8fb4-765d7b4204cc["Output\nSGPS Distinct Peptides"]; 24 --> b6c61697-ff52-43c0-8fb4-765d7b4204cc; style b6c61697-ff52-43c0-8fb4-765d7b4204cc stroke:#2c3143,stroke-width:4px; 25["SGPS-MQ Peptides"]; 21 -->|out_file1| 25; 24 -->|out_file1| 25; a8c2de2e-e322-4830-9d28-2f79bf937013["Output\nSGPS-MQ Peptides"]; 25 --> a8c2de2e-e322-4830-9d28-2f79bf937013; style a8c2de2e-e322-4830-9d28-2f79bf937013 stroke:#2c3143,stroke-width:4px; 26["Distinct Peptides"]; 25 -->|out_file1| 26; ef0d91b1-042f-4a9f-a2b6-bf73d82f24f7["Output\nDistinct Peptides"]; 26 --> ef0d91b1-042f-4a9f-a2b6-bf73d82f24f7; style ef0d91b1-042f-4a9f-a2b6-bf73d82f24f7 stroke:#2c3143,stroke-width:4px;
Inputs
Input | Label |
---|---|
Input dataset | Human UniProt Microbial Proteins (from MetaNovo) and cRAP |
Input dataset collection | RAW files (Dataset Collection) |
Input dataset | Experimental Design Discovery MaxQuant |
Outputs
From | Output | Label |
---|---|---|
toolshed.g2.bx.psu.edu/repos/galaxyp/peptideshaker/ident_params/4.0.41+galaxy1 | Identification Parameters | Identification Parameters: PAR file |
toolshed.g2.bx.psu.edu/repos/galaxyp/dbbuilder/dbbuilder/0.3.4 | Protein Database Downloader | Human SwissProt (reviewed only) |
toolshed.g2.bx.psu.edu/repos/galaxyp/fasta_merge_files_and_filter_unique_sequences/fasta_merge_files_and_filter_unique_sequences/1.2.0 | FASTA Merge Files and Filter Unique Sequences | Human SwissProt+cRAP |
toolshed.g2.bx.psu.edu/repos/galaxyp/maxquant/maxquant/2.0.3.0+galaxy0 | MaxQuant | |
Grep1 | Select | Select microbial peptides (MQ) |
toolshed.g2.bx.psu.edu/repos/galaxyp/peptideshaker/peptide_shaker/2.0.33+galaxy1 | Peptide Shaker | |
Grep1 | Select | Select microbial peptides (SGPS) |
Filter1 | Filter | Filter confident microbial peptides |
Filter1 | Filter | Filter confident microbial PSMs |
Grouping1 | Group | MQ Distinct Peptides |
Grouping1 | Group | SGPS Distinct Peptides |
toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1 | Concatenate datasets | SGPS-MQ Peptides |
Grouping1 | Group | Distinct Peptides |
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:
Version History
Version | Commit | Time | Comments |
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For Admins
Installing the workflow tools
wget https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/clinical-mp-2-discovery/workflows/WF2_Discovery-Workflow.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