Clustering 3k PBMC with Scanpy

Run Workflow in Galaxy

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

flowchart TD
  0["ℹ️ Input Dataset\nBarcodes"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nGenes"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\nMatrix"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["ℹ️ Input Dataset\nmito header"];
  style 3 stroke:#2c3143,stroke-width:4px;
  4["Import Anndata and loom"];
  2 -->|output| 4;
  0 -->|output| 4;
  1 -->|output| 4;
  5["Inspect AnnData"];
  4 -->|anndata| 5;
  6["Inspect AnnData"];
  4 -->|anndata| 6;
  7["Inspect AnnData"];
  4 -->|anndata| 7;
  8["Filter"];
  4 -->|anndata| 8;
  9["Inspect AnnData"];
  4 -->|anndata| 9;
  10["Inspect AnnData"];
  8 -->|anndata_out| 10;
  11["Select last"];
  10 -->|var| 11;
  12["Text reformatting"];
  11 -->|outfile| 12;
  13["Search in textfiles"];
  11 -->|outfile| 13;
  14["Replace Text"];
  12 -->|outfile| 14;
  15["Concatenate datasets"];
  3 -->|output| 15;
  14 -->|outfile| 15;
  16["Manipulate AnnData"];
  8 -->|anndata_out| 16;
  15 -->|out_file1| 16;
  17["Inspect and manipulate"];
  16 -->|anndata| 17;
  18["Inspect AnnData"];
  16 -->|anndata| 18;
  19["Plot"];
  17 -->|anndata_out| 19;
  4ab8b810-4e79-46b2-b740-74e267f5e209["Output\nout_png"];
  19 --> 4ab8b810-4e79-46b2-b740-74e267f5e209;
  style 4ab8b810-4e79-46b2-b740-74e267f5e209 stroke:#2c3143,stroke-width:4px;
  20["Filter"];
  17 -->|anndata_out| 20;
  21["Plot"];
  17 -->|anndata_out| 21;
  02478047-eb04-4a4e-b1ff-f3cb3c7673d5["Output\nout_png"];
  21 --> 02478047-eb04-4a4e-b1ff-f3cb3c7673d5;
  style 02478047-eb04-4a4e-b1ff-f3cb3c7673d5 stroke:#2c3143,stroke-width:4px;
  22["Plot"];
  17 -->|anndata_out| 22;
  3eb66a4a-79fe-43a3-889b-d43daeae5e17["Output\nout_png"];
  22 --> 3eb66a4a-79fe-43a3-889b-d43daeae5e17;
  style 3eb66a4a-79fe-43a3-889b-d43daeae5e17 stroke:#2c3143,stroke-width:4px;
  23["Filter"];
  20 -->|anndata_out| 23;
  24["Manipulate AnnData"];
  23 -->|anndata_out| 24;
  25["Normalize"];
  24 -->|anndata| 25;
  26["Inspect and manipulate"];
  25 -->|anndata_out| 26;
  27["Manipulate AnnData"];
  26 -->|anndata_out| 27;
  28["Filter"];
  27 -->|anndata| 28;
  29["Manipulate AnnData"];
  28 -->|anndata_out| 29;
  30["Plot"];
  28 -->|anndata_out| 30;
  31["Remove confounders"];
  29 -->|anndata| 31;
  32["Inspect and manipulate"];
  31 -->|anndata_out| 32;
  33["Cluster, infer trajectories and embed"];
  32 -->|anndata_out| 33;
  96cbb37e-e755-4479-9f14-f0e14f689868["Output\nanndata_out"];
  33 --> 96cbb37e-e755-4479-9f14-f0e14f689868;
  style 96cbb37e-e755-4479-9f14-f0e14f689868 stroke:#2c3143,stroke-width:4px;
  34["Plot"];
  33 -->|anndata_out| 34;
  35["Plot"];
  33 -->|anndata_out| 35;
  5dc45ef9-c56e-4dbd-9817-367c981a2041["Output\nout_png"];
  35 --> 5dc45ef9-c56e-4dbd-9817-367c981a2041;
  style 5dc45ef9-c56e-4dbd-9817-367c981a2041 stroke:#2c3143,stroke-width:4px;
  36["Inspect and manipulate"];
  33 -->|anndata_out| 36;
  37["Plot"];
  33 -->|anndata_out| 37;
  38["Plot"];
  33 -->|anndata_out| 38;
  39["Cluster, infer trajectories and embed"];
  36 -->|anndata_out| 39;
  40["Cluster, infer trajectories and embed"];
  39 -->|anndata_out| 40;
  41["Plot"];
  39 -->|anndata_out| 41;
  29513947-d16c-48b2-93ff-dd78cd99ecb7["Output\nout_png"];
  41 --> 29513947-d16c-48b2-93ff-dd78cd99ecb7;
  style 29513947-d16c-48b2-93ff-dd78cd99ecb7 stroke:#2c3143,stroke-width:4px;
  42["Inspect and manipulate"];
  40 -->|anndata_out| 42;
  43["Inspect and manipulate"];
  40 -->|anndata_out| 43;
  da91ad5a-dd9c-482e-accc-8e42d645e7b1["Output\nanndata_out"];
  43 --> da91ad5a-dd9c-482e-accc-8e42d645e7b1;
  style da91ad5a-dd9c-482e-accc-8e42d645e7b1 stroke:#2c3143,stroke-width:4px;
  44["Plot"];
  40 -->|anndata_out| 44;
  45["Inspect AnnData"];
  42 -->|anndata_out| 45;
  868797a3-ab74-45bf-96d1-84451a16f882["Output\nuns_rank_genes_groups_names"];
  45 --> 868797a3-ab74-45bf-96d1-84451a16f882;
  style 868797a3-ab74-45bf-96d1-84451a16f882 stroke:#2c3143,stroke-width:4px;
  46["Plot"];
  42 -->|anndata_out| 46;
  47["Plot"];
  43 -->|anndata_out| 47;
  2d042636-8fd1-42e3-af8d-83b4d613f075["Output\nout_png"];
  47 --> 2d042636-8fd1-42e3-af8d-83b4d613f075;
  style 2d042636-8fd1-42e3-af8d-83b4d613f075 stroke:#2c3143,stroke-width:4px;
  48["Manipulate AnnData"];
  43 -->|anndata_out| 48;
  51289df3-101f-4c6c-ae85-a8f46c2f33ea["Output\nanndata"];
  48 --> 51289df3-101f-4c6c-ae85-a8f46c2f33ea;
  style 51289df3-101f-4c6c-ae85-a8f46c2f33ea stroke:#2c3143,stroke-width:4px;
  49["Inspect and manipulate"];
  43 -->|anndata_out| 49;
  50["Inspect AnnData"];
  43 -->|anndata_out| 50;
  e617acd1-e59d-4f20-b39d-9dc0f832b0db["Output\nuns_rank_genes_groups_names"];
  50 --> e617acd1-e59d-4f20-b39d-9dc0f832b0db;
  style e617acd1-e59d-4f20-b39d-9dc0f832b0db stroke:#2c3143,stroke-width:4px;
  51["Plot"];
  43 -->|anndata_out| 51;
  983e7cee-7028-456c-9db2-bf0ad3e52de5["Output\nout_png"];
  51 --> 983e7cee-7028-456c-9db2-bf0ad3e52de5;
  style 983e7cee-7028-456c-9db2-bf0ad3e52de5 stroke:#2c3143,stroke-width:4px;
  52["Inspect clusters"];
  43 -->|anndata_out| 52;
  53["Plot"];
  43 -->|anndata_out| 53;
  734099bb-f454-4d8c-bc78-a269b0570c41["Output\nout_png"];
  53 --> 734099bb-f454-4d8c-bc78-a269b0570c41;
  style 734099bb-f454-4d8c-bc78-a269b0570c41 stroke:#2c3143,stroke-width:4px;
  54["Plot"];
  43 -->|anndata_out| 54;
  55["Plot"];
  43 -->|anndata_out| 55;
  39f2d4b6-f2e8-41b3-a00a-a2c5b54face2["Output\nout_png"];
  55 --> 39f2d4b6-f2e8-41b3-a00a-a2c5b54face2;
  style 39f2d4b6-f2e8-41b3-a00a-a2c5b54face2 stroke:#2c3143,stroke-width:4px;
  56["Plot"];
  48 -->|anndata| 56;
  e0979d1e-eb87-4a7b-904f-a5116c7b8fff["Output\nout_svg"];
  56 --> e0979d1e-eb87-4a7b-904f-a5116c7b8fff;
  style e0979d1e-eb87-4a7b-904f-a5116c7b8fff stroke:#2c3143,stroke-width:4px;
  57["Plot"];
  48 -->|anndata| 57;
  58["Plot"];
  48 -->|anndata| 58;
  bd14e644-2a32-4a81-bd83-042ee46d118a["Output\nout_png"];
  58 --> bd14e644-2a32-4a81-bd83-042ee46d118a;
  style bd14e644-2a32-4a81-bd83-042ee46d118a stroke:#2c3143,stroke-width:4px;
  59["Plot"];
  49 -->|anndata_out| 59;
  e9cf90db-ac42-4876-8abd-183fea271666["Output\ncollection_png"];
  59 --> e9cf90db-ac42-4876-8abd-183fea271666;
  style e9cf90db-ac42-4876-8abd-183fea271666 stroke:#2c3143,stroke-width:4px;
  60["Plot"];
  49 -->|anndata_out| 60;
  aef215b1-dbb4-447b-9297-c90536842c8e["Output\nout_png"];
  60 --> aef215b1-dbb4-447b-9297-c90536842c8e;
  style aef215b1-dbb4-447b-9297-c90536842c8e stroke:#2c3143,stroke-width:4px;
  61["Datamash"];
  52 -->|obs| 61;

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/single-cell/tutorials/scrna-scanpy-pbmc3k/workflows/Clustering-3k-PBMC-with-Scanpy.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