Gene-based Pathogen Identification

Run Workflow in Galaxy

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

flowchart TD
  0["ℹ️ Input Collection\ncollection_of_preprocessed_samples"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["Extract element identifiers"];
  0 -->|output| 1;
  d82a93c6-23a9-4f85-879c-ecd759a31087["Output\nextracted_samples_IDs"];
  1 --> d82a93c6-23a9-4f85-879c-ecd759a31087;
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  2["Build list"];
  0 -->|output| 2;
  f5b5b256-8ddf-4da8-8111-b1f6d3025a0d["Output\nlist_of_lists_of_preprocessed_samples"];
  2 --> f5b5b256-8ddf-4da8-8111-b1f6d3025a0d;
  style f5b5b256-8ddf-4da8-8111-b1f6d3025a0d stroke:#2c3143,stroke-width:4px;
  3["Split file"];
  1 -->|output| 3;
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  4["Flye"];
  2 -->|output| 4;
  ff0d8c7b-2ac7-4c6d-a110-f71418dad938["Output\nflye_consensus_fasta"];
  4 --> ff0d8c7b-2ac7-4c6d-a110-f71418dad938;
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  2385436f-fbe8-4d77-a40b-27a097d02941["Output\nflye_assembly_graph"];
  4 --> 2385436f-fbe8-4d77-a40b-27a097d02941;
  style 2385436f-fbe8-4d77-a40b-27a097d02941 stroke:#2c3143,stroke-width:4px;
  0e42ce51-c46b-45d8-baa4-45c0e98ac712["Output\nflye_assembly_gfa"];
  4 --> 0e42ce51-c46b-45d8-baa4-45c0e98ac712;
  style 0e42ce51-c46b-45d8-baa4-45c0e98ac712 stroke:#2c3143,stroke-width:4px;
  3f297aed-7cee-4999-bbf4-69d84de6b64f["Output\nflye_assembly_info_tabular"];
  4 --> 3f297aed-7cee-4999-bbf4-69d84de6b64f;
  style 3f297aed-7cee-4999-bbf4-69d84de6b64f stroke:#2c3143,stroke-width:4px;
  5["Parse parameter value"];
  3 -->|list_output_txt| 5;
  3608e170-c462-42a2-8003-f3f65baa3834["Output\nparsed_extracted_samples_IDs_to_text"];
  5 --> 3608e170-c462-42a2-8003-f3f65baa3834;
  style 3608e170-c462-42a2-8003-f3f65baa3834 stroke:#2c3143,stroke-width:4px;
  6["medaka consensus pipeline"];
  4 -->|consensus| 6;
  0 -->|output| 6;
  9e5ad6ec-b408-4132-ba07-dec9fa626923["Output\nmedaka_gaps_in_draft_bed_file"];
  6 --> 9e5ad6ec-b408-4132-ba07-dec9fa626923;
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  fcbd3e3f-2e93-4798-b696-dad7db9f2efd["Output\nmedaka_log_file"];
  6 --> fcbd3e3f-2e93-4798-b696-dad7db9f2efd;
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  60656aac-ad2a-4c9b-9a68-b9fb18ae5595["Output\nmedaka_propability_h5_file"];
  6 --> 60656aac-ad2a-4c9b-9a68-b9fb18ae5595;
  style 60656aac-ad2a-4c9b-9a68-b9fb18ae5595 stroke:#2c3143,stroke-width:4px;
  c790d434-8e78-4df0-a0d4-8f9da0692158["Output\nmedaka_calls_of_draft_bam_file"];
  6 --> c790d434-8e78-4df0-a0d4-8f9da0692158;
  style c790d434-8e78-4df0-a0d4-8f9da0692158 stroke:#2c3143,stroke-width:4px;
  df361e19-b6d1-405b-96cc-b48c1ab7c604["Output\nsample_all_contigs"];
  6 --> df361e19-b6d1-405b-96cc-b48c1ab7c604;
  style df361e19-b6d1-405b-96cc-b48c1ab7c604 stroke:#2c3143,stroke-width:4px;
  7["Bandage Image"];
  4 -->|assembly_gfa| 7;
  9612a851-1f94-4d54-b001-5d082bcc9055["Output\nbandage_assembly_graph_image"];
  7 --> 9612a851-1f94-4d54-b001-5d082bcc9055;
  style 9612a851-1f94-4d54-b001-5d082bcc9055 stroke:#2c3143,stroke-width:4px;
  8["Compose text parameter value"];
  5 -->|text_param| 8;
  9["FASTA-to-Tabular"];
  6 -->|out_consensus| 9;
  de06c362-5b0a-4c29-956e-fbf02539789a["Output\nsample_specific_contigs_tabular_file_preparation"];
  9 --> de06c362-5b0a-4c29-956e-fbf02539789a;
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  10["ABRicate"];
  6 -->|out_consensus| 10;
  8f227fc7-2d92-4c6f-af64-e841c1315b4f["Output\nabricate_with_vfdb_to_identify_genes_with_VFs"];
  10 --> 8f227fc7-2d92-4c6f-af64-e841c1315b4f;
  style 8f227fc7-2d92-4c6f-af64-e841c1315b4f stroke:#2c3143,stroke-width:4px;
  11["ABRicate"];
  6 -->|out_consensus| 11;
  fa021d98-d885-4834-ac62-f30d5792260e["Output\nabricate_report_using_ncbi_database_to_indentify_amr"];
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  12["Replace"];
  8 -->|out1| 12;
  9 -->|output| 12;
  174cb2c3-ed28-453c-8afb-85150e0b51ad["Output\nsample_specific_contigs_tabular_file"];
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  13["Replace"];
  8 -->|out1| 13;
  10 -->|report| 13;
  19e56e00-6eef-4a4e-9cc6-d93dbf9420ad["Output\nvfs"];
  13 --> 19e56e00-6eef-4a4e-9cc6-d93dbf9420ad;
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  14["Replace"];
  8 -->|out1| 14;
  11 -->|report| 14;
  a8eb74a5-362b-4f0f-a944-672e27981a41["Output\namrs"];
  14 --> a8eb74a5-362b-4f0f-a944-672e27981a41;
  style a8eb74a5-362b-4f0f-a944-672e27981a41 stroke:#2c3143,stroke-width:4px;
  15["Tabular-to-FASTA"];
  12 -->|outfile| 15;
  a5bb1cbe-1bde-49a1-ad86-6d57b1319fbe["Output\ncontigs"];
  15 --> a5bb1cbe-1bde-49a1-ad86-6d57b1319fbe;
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Inputs

Outputs

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

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/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/gene_based_pathogen_identification.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