Trajectory analysis using Monocle3 - full tutorial workflow

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flowchart TD
  0["ℹ️ Input Dataset\nAnnData to extract genes & cells annotations"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nAnnData before processing to extract clean expression matrix"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["Extract cell annotations"];
  0 -->|output| 2;
  0646798d-3a5d-420a-a7cf-cde6cec722d5["Output\nExtracted cell annotations (obs)"];
  2 --> 0646798d-3a5d-420a-a7cf-cde6cec722d5;
  style 0646798d-3a5d-420a-a7cf-cde6cec722d5 stroke:#2c3143,stroke-width:4px;
  3["Extract gene annotations"];
  0 -->|output| 3;
  84162745-68b0-41a5-b06e-a285440ba095["Output\nExtracted gene annotations (var)"];
  3 --> 84162745-68b0-41a5-b06e-a285440ba095;
  style 84162745-68b0-41a5-b06e-a285440ba095 stroke:#2c3143,stroke-width:4px;
  4["Extract clean expression matrix"];
  1 -->|output| 4;
  3f03af0c-ac41-4450-b5ba-639a79ea543b["Output\nUnprocessed expression matrix"];
  4 --> 3f03af0c-ac41-4450-b5ba-639a79ea543b;
  style 3f03af0c-ac41-4450-b5ba-639a79ea543b stroke:#2c3143,stroke-width:4px;
  5["Filter out macrophages"];
  2 -->|obs| 5;
  fb81e9a1-0603-419a-83f5-0c9f94939b16["Output\nCells without macrophages"];
  5 --> fb81e9a1-0603-419a-83f5-0c9f94939b16;
  style fb81e9a1-0603-419a-83f5-0c9f94939b16 stroke:#2c3143,stroke-width:4px;
  6["gene_short_name annotation"];
  3 -->|var| 6;
  94a60e6c-cdf7-48e5-8b55-d221cef22688["Output\nGenes table with gene_short_name colname"];
  6 --> 94a60e6c-cdf7-48e5-8b55-d221cef22688;
  style 94a60e6c-cdf7-48e5-8b55-d221cef22688 stroke:#2c3143,stroke-width:4px;
  7["Cut cells IDs"];
  5 -->|out_file1| 7;
  34146c30-2666-481f-8d49-a849d5d3aa91["Output\nFiltered cells IDs "];
  7 --> 34146c30-2666-481f-8d49-a849d5d3aa91;
  style 34146c30-2666-481f-8d49-a849d5d3aa91 stroke:#2c3143,stroke-width:4px;
  8["Cut genes IDs"];
  6 -->|out_file1| 8;
  8f38fb93-cb30-4fbc-90c5-7f6bd023feea["Output\nGenes IDs"];
  8 --> 8f38fb93-cb30-4fbc-90c5-7f6bd023feea;
  style 8f38fb93-cb30-4fbc-90c5-7f6bd023feea stroke:#2c3143,stroke-width:4px;
  9["Filter matrix by cells"];
  7 -->|out_file1| 9;
  4 -->|X| 9;
  f654c045-5fea-43f9-96d6-492c810593d2["Output\nPre-filtered matrix (by cells)"];
  9 --> f654c045-5fea-43f9-96d6-492c810593d2;
  style f654c045-5fea-43f9-96d6-492c810593d2 stroke:#2c3143,stroke-width:4px;
  10["Remove duplicate column cells IDs"];
  9 -->|out_file1| 10;
  f633c125-a4d0-4fa7-ab87-022349f4ac70["Output\nFiltered matrix (by cells) "];
  10 --> f633c125-a4d0-4fa7-ab87-022349f4ac70;
  style f633c125-a4d0-4fa7-ab87-022349f4ac70 stroke:#2c3143,stroke-width:4px;
  11["Transpose matrix"];
  10 -->|output| 11;
  3202091e-1afc-4f50-8922-1f9e50c490fc["Output\nfiltered matrix (by cells) transposed"];
  11 --> 3202091e-1afc-4f50-8922-1f9e50c490fc;
  style 3202091e-1afc-4f50-8922-1f9e50c490fc stroke:#2c3143,stroke-width:4px;
  12["Filter matrix by genes"];
  8 -->|out_file1| 12;
  11 -->|out_file| 12;
  6c23cbd5-a1b5-428e-8ff9-ebac4893ad88["Output\nPre-filtered matrix (by cells & genes)"];
  12 --> 6c23cbd5-a1b5-428e-8ff9-ebac4893ad88;
  style 6c23cbd5-a1b5-428e-8ff9-ebac4893ad88 stroke:#2c3143,stroke-width:4px;
  13["Remove duplicate column genes IDs"];
  12 -->|out_file1| 13;
  25839326-0b5d-4e74-91ec-24e22c08f7c5["Output\nFiltered matrix (by cells & genes)"];
  13 --> 25839326-0b5d-4e74-91ec-24e22c08f7c5;
  style 25839326-0b5d-4e74-91ec-24e22c08f7c5 stroke:#2c3143,stroke-width:4px;
  14["Monocle3 create"];
  5 -->|out_file1| 14;
  13 -->|output| 14;
  6 -->|out_file1| 14;
  f8c5589c-a70d-416e-a9de-ebc987f61fc3["Output\nMonocle3 create on input dataset(s): cds3"];
  14 --> f8c5589c-a70d-416e-a9de-ebc987f61fc3;
  style f8c5589c-a70d-416e-a9de-ebc987f61fc3 stroke:#2c3143,stroke-width:4px;
  15["Monocle3 preprocess"];
  14 -->|output_rds| 15;
  c134942f-60e7-4cd0-8c32-da4a303b879d["Output\nMonocle3 preprocess on input dataset(s): cds3"];
  15 --> c134942f-60e7-4cd0-8c32-da4a303b879d;
  style c134942f-60e7-4cd0-8c32-da4a303b879d stroke:#2c3143,stroke-width:4px;
  16["Monocle3 reduceDim"];
  15 -->|output_rds| 16;
  2c9fb108-2a1c-41df-a8d8-81a18b66d2a1["Output\nMonocle3 reduceDim on input dataset(s): cds3"];
  16 --> 2c9fb108-2a1c-41df-a8d8-81a18b66d2a1;
  style 2c9fb108-2a1c-41df-a8d8-81a18b66d2a1 stroke:#2c3143,stroke-width:4px;
  17["Monocle3 partition"];
  16 -->|output_rds| 17;
  93371c10-6583-47fc-830f-9a90dc980766["Output\nMonocle3 partition on input dataset(s): cds3"];
  17 --> 93371c10-6583-47fc-830f-9a90dc980766;
  style 93371c10-6583-47fc-830f-9a90dc980766 stroke:#2c3143,stroke-width:4px;
  18["Plot cell type"];
  16 -->|output_rds| 18;
  f096d060-82e8-4847-9e8f-b22c9288f565["Output\nCell type plot"];
  18 --> f096d060-82e8-4847-9e8f-b22c9288f565;
  style f096d060-82e8-4847-9e8f-b22c9288f565 stroke:#2c3143,stroke-width:4px;
  19["Plot genotype"];
  16 -->|output_rds| 19;
  aab28bb1-e2e7-4b7d-9b2b-1cab64bea287["Output\nGenotype plot"];
  19 --> aab28bb1-e2e7-4b7d-9b2b-1cab64bea287;
  style aab28bb1-e2e7-4b7d-9b2b-1cab64bea287 stroke:#2c3143,stroke-width:4px;
  20["Plot batch"];
  16 -->|output_rds| 20;
  9b362eee-9238-47c5-a4c2-85f3995430f4["Output\nBatch plot"];
  20 --> 9b362eee-9238-47c5-a4c2-85f3995430f4;
  style 9b362eee-9238-47c5-a4c2-85f3995430f4 stroke:#2c3143,stroke-width:4px;
  21["Plot sex"];
  16 -->|output_rds| 21;
  c2a1e104-ef2d-4b66-ac2b-bf0251714434["Output\nSex plot"];
  21 --> c2a1e104-ef2d-4b66-ac2b-bf0251714434;
  style c2a1e104-ef2d-4b66-ac2b-bf0251714434 stroke:#2c3143,stroke-width:4px;
  22["Monocle3 top markers"];
  17 -->|output_rds| 22;
  23["Plot genes"];
  17 -->|output_rds| 23;
  e8867379-82c6-4c32-a2d3-0b24670269ae["Output\nGene expression plot"];
  23 --> e8867379-82c6-4c32-a2d3-0b24670269ae;
  style e8867379-82c6-4c32-a2d3-0b24670269ae stroke:#2c3143,stroke-width:4px;
  24["Plot partition"];
  17 -->|output_rds| 24;
  3f7b0a7c-85d6-430b-8385-fa9a76385c0e["Output\nPartition plot"];
  24 --> 3f7b0a7c-85d6-430b-8385-fa9a76385c0e;
  style 3f7b0a7c-85d6-430b-8385-fa9a76385c0e stroke:#2c3143,stroke-width:4px;
  25["Plot cluster"];
  17 -->|output_rds| 25;
  40b65826-f73e-4054-a56d-b241985d6996["Output\nCluster plot"];
  25 --> 40b65826-f73e-4054-a56d-b241985d6996;
  style 40b65826-f73e-4054-a56d-b241985d6996 stroke:#2c3143,stroke-width:4px;
  26["Monocle3 learnGraph"];
  17 -->|output_rds| 26;
  294b1a49-cec6-49d0-bcd4-3a954da67bec["Output\nMonocle3 learnGraph on input dataset(s): cds3"];
  26 --> 294b1a49-cec6-49d0-bcd4-3a954da67bec;
  style 294b1a49-cec6-49d0-bcd4-3a954da67bec stroke:#2c3143,stroke-width:4px;
  27["Plot learned trajectory"];
  26 -->|output_rds| 27;
  c85ddefe-8eaf-4d21-93ed-ca0859286bf0["Output\nCell types & learned trajectory path plot"];
  27 --> c85ddefe-8eaf-4d21-93ed-ca0859286bf0;
  style c85ddefe-8eaf-4d21-93ed-ca0859286bf0 stroke:#2c3143,stroke-width:4px;
  28["Monocle3 orderCells"];
  26 -->|output_rds| 28;
  5aea5752-b767-4fc8-8741-1f4d1c659a41["Output\nMonocle3 orderCells on input dataset(s): cds3"];
  28 --> 5aea5752-b767-4fc8-8741-1f4d1c659a41;
  style 5aea5752-b767-4fc8-8741-1f4d1c659a41 stroke:#2c3143,stroke-width:4px;
  29["Monocle3 diffExp"];
  28 -->|output_rds| 29;
  3c298624-9f06-4e52-b2a8-fb834b87c296["Output\nDifferential expression of genes - table"];
  29 --> 3c298624-9f06-4e52-b2a8-fb834b87c296;
  style 3c298624-9f06-4e52-b2a8-fb834b87c296 stroke:#2c3143,stroke-width:4px;
  30["Plot pseudotime"];
  28 -->|output_rds| 30;
  813d15bb-0771-4aed-9226-4874c1ddba59["Output\nPseudotime plot"];
  30 --> 813d15bb-0771-4aed-9226-4874c1ddba59;
  style 813d15bb-0771-4aed-9226-4874c1ddba59 stroke:#2c3143,stroke-width:4px;

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/single-cell/tutorials/scrna-case_monocle3-trajectories/workflows/Trajectory-analysis-using-Monocle3---full-tutorial-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