Workflows

These workflows are associated with Inferring single cell trajectories with Monocle3

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.

AnnData object to Monocle input files

Last updated Nov 18, 2022

Launch in Tutorial Mode question
License: None Specified, defaults to CC-BY-4.0
Tests: ❌ Results: Not yet automated

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;
  9d66a217-4269-4fb4-9a4e-520eedbb0c9d["Output\nExtracted cell annotations (obs)"];
  2 --> 9d66a217-4269-4fb4-9a4e-520eedbb0c9d;
  style 9d66a217-4269-4fb4-9a4e-520eedbb0c9d stroke:#2c3143,stroke-width:4px;
  3["Extract gene annotations"];
  0 -->|output| 3;
  03537e97-d668-4ce2-ba6b-2952a18a2752["Output\nExtracted gene annotations (var)"];
  3 --> 03537e97-d668-4ce2-ba6b-2952a18a2752;
  style 03537e97-d668-4ce2-ba6b-2952a18a2752 stroke:#2c3143,stroke-width:4px;
  4["Extract clean expression matrix"];
  1 -->|output| 4;
  963462c8-4ae0-486c-8173-d98339127850["Output\nUnprocessed expression matrix"];
  4 --> 963462c8-4ae0-486c-8173-d98339127850;
  style 963462c8-4ae0-486c-8173-d98339127850 stroke:#2c3143,stroke-width:4px;
  5["Filter out unwanted cell types"];
  2 -->|obs| 5;
  5dcb7029-8d03-445d-bb3e-a3119e502be4["Output\nCells without macrophages"];
  5 --> 5dcb7029-8d03-445d-bb3e-a3119e502be4;
  style 5dcb7029-8d03-445d-bb3e-a3119e502be4 stroke:#2c3143,stroke-width:4px;
  6["gene_short_name annotation"];
  3 -->|var| 6;
  15fd415b-2d73-4a1d-92ad-200bb2e73853["Output\nGenes table with gene_short_name colname"];
  6 --> 15fd415b-2d73-4a1d-92ad-200bb2e73853;
  style 15fd415b-2d73-4a1d-92ad-200bb2e73853 stroke:#2c3143,stroke-width:4px;
  7["Cut cells IDs"];
  5 -->|out_file1| 7;
  f9bde249-43b9-4424-8285-e437549223e2["Output\nFiltered cells IDs "];
  7 --> f9bde249-43b9-4424-8285-e437549223e2;
  style f9bde249-43b9-4424-8285-e437549223e2 stroke:#2c3143,stroke-width:4px;
  8["Cut genes IDs"];
  6 -->|out_file1| 8;
  b22efa1d-db99-435f-9357-74150ac9a437["Output\nGenes IDs"];
  8 --> b22efa1d-db99-435f-9357-74150ac9a437;
  style b22efa1d-db99-435f-9357-74150ac9a437 stroke:#2c3143,stroke-width:4px;
  9["Filter matrix by cells"];
  7 -->|out_file1| 9;
  4 -->|X| 9;
  b45f18b6-e385-41a1-a8f0-f94e6616e2b3["Output\nPre-filtered matrix (by cells)"];
  9 --> b45f18b6-e385-41a1-a8f0-f94e6616e2b3;
  style b45f18b6-e385-41a1-a8f0-f94e6616e2b3 stroke:#2c3143,stroke-width:4px;
  10["Remove duplicate column cells IDs"];
  9 -->|out_file1| 10;
  f4d6a581-9b42-41dc-9a4a-278fe5d6591c["Output\nFiltered matrix (by cells) "];
  10 --> f4d6a581-9b42-41dc-9a4a-278fe5d6591c;
  style f4d6a581-9b42-41dc-9a4a-278fe5d6591c stroke:#2c3143,stroke-width:4px;
  11["Transpose matrix"];
  10 -->|output| 11;
  e4eb8fb3-2028-41fb-8aca-b1c0a6e6bfe5["Output\nfiltered matrix (by cells) transposed"];
  11 --> e4eb8fb3-2028-41fb-8aca-b1c0a6e6bfe5;
  style e4eb8fb3-2028-41fb-8aca-b1c0a6e6bfe5 stroke:#2c3143,stroke-width:4px;
  12["Filter matrix by genes"];
  8 -->|out_file1| 12;
  11 -->|out_file| 12;
  c0481255-0187-407c-9f29-f4c0069d9285["Output\nPre-filtered matrix (by cells & genes)"];
  12 --> c0481255-0187-407c-9f29-f4c0069d9285;
  style c0481255-0187-407c-9f29-f4c0069d9285 stroke:#2c3143,stroke-width:4px;
  13["Remove duplicate column genes IDs"];
  12 -->|out_file1| 13;
  4dcd8e60-1298-4886-be8f-af1eac9f20f7["Output\nFiltered matrix (by cells & genes)"];
  13 --> 4dcd8e60-1298-4886-be8f-af1eac9f20f7;
  style 4dcd8e60-1298-4886-be8f-af1eac9f20f7 stroke:#2c3143,stroke-width:4px;

Monocle3 workflow

Last updated Nov 18, 2022

Launch in Tutorial Mode question
License: None Specified, defaults to CC-BY-4.0
Tests: ❌ Results: Not yet automated

flowchart TD
  0["ℹ️ Input Dataset\nExpression matrix input"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nCell annotations input"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\nGene annotations input"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["Monocle3 create"];
  1 -->|output| 3;
  0 -->|output| 3;
  2 -->|output| 3;
  30db218d-f9e5-426d-ac9b-7823743ab5fb["Output\nMonocle3 create on input dataset(s): cds3"];
  3 --> 30db218d-f9e5-426d-ac9b-7823743ab5fb;
  style 30db218d-f9e5-426d-ac9b-7823743ab5fb stroke:#2c3143,stroke-width:4px;
  4["Monocle3 preprocess"];
  3 -->|output_rds| 4;
  38996ee0-0c00-4a01-ad18-f2e505eaf780["Output\nMonocle3 preprocess on input dataset(s): cds3"];
  4 --> 38996ee0-0c00-4a01-ad18-f2e505eaf780;
  style 38996ee0-0c00-4a01-ad18-f2e505eaf780 stroke:#2c3143,stroke-width:4px;
  5["Monocle3 reduceDim"];
  4 -->|output_rds| 5;
  21edf68f-72df-457d-aad7-c5fc5afa2b6b["Output\nMonocle3 reduceDim on input dataset(s): cds3"];
  5 --> 21edf68f-72df-457d-aad7-c5fc5afa2b6b;
  style 21edf68f-72df-457d-aad7-c5fc5afa2b6b stroke:#2c3143,stroke-width:4px;
  6["Monocle3 partition"];
  5 -->|output_rds| 6;
  fdb0e520-27c4-43a0-8f27-a25832a0816d["Output\nMonocle3 partition on input dataset(s): cds3"];
  6 --> fdb0e520-27c4-43a0-8f27-a25832a0816d;
  style fdb0e520-27c4-43a0-8f27-a25832a0816d stroke:#2c3143,stroke-width:4px;
  7["Plot cell type"];
  5 -->|output_rds| 7;
  5e309658-e20f-4da1-8841-818f16fa8f01["Output\nCell type plot"];
  7 --> 5e309658-e20f-4da1-8841-818f16fa8f01;
  style 5e309658-e20f-4da1-8841-818f16fa8f01 stroke:#2c3143,stroke-width:4px;
  8["Plot genotype"];
  5 -->|output_rds| 8;
  aca3b2c0-2d3b-4a4e-8732-cf6ddc7844a4["Output\nGenotype plot"];
  8 --> aca3b2c0-2d3b-4a4e-8732-cf6ddc7844a4;
  style aca3b2c0-2d3b-4a4e-8732-cf6ddc7844a4 stroke:#2c3143,stroke-width:4px;
  9["Plot batch"];
  5 -->|output_rds| 9;
  c8eec2e4-1a64-47bb-812b-4002968c57c8["Output\nBatch plot"];
  9 --> c8eec2e4-1a64-47bb-812b-4002968c57c8;
  style c8eec2e4-1a64-47bb-812b-4002968c57c8 stroke:#2c3143,stroke-width:4px;
  10["Plot sex"];
  5 -->|output_rds| 10;
  c75954dd-34d5-4a20-bcf3-e5cd92d74885["Output\nSex plot"];
  10 --> c75954dd-34d5-4a20-bcf3-e5cd92d74885;
  style c75954dd-34d5-4a20-bcf3-e5cd92d74885 stroke:#2c3143,stroke-width:4px;
  11["Monocle3 top markers"];
  6 -->|output_rds| 11;
  12["Plot genes"];
  6 -->|output_rds| 12;
  f91c22a3-8c6d-432a-92c5-cb010115fa86["Output\nGene expression plot"];
  12 --> f91c22a3-8c6d-432a-92c5-cb010115fa86;
  style f91c22a3-8c6d-432a-92c5-cb010115fa86 stroke:#2c3143,stroke-width:4px;
  13["Plot partition"];
  6 -->|output_rds| 13;
  f4c5f89b-edd7-489c-b4a2-a7a3e7d6a89d["Output\nPartition plot"];
  13 --> f4c5f89b-edd7-489c-b4a2-a7a3e7d6a89d;
  style f4c5f89b-edd7-489c-b4a2-a7a3e7d6a89d stroke:#2c3143,stroke-width:4px;
  14["Plot cluster"];
  6 -->|output_rds| 14;
  a2c1a628-d79d-4e37-ad33-de92033021a8["Output\nCluster plot"];
  14 --> a2c1a628-d79d-4e37-ad33-de92033021a8;
  style a2c1a628-d79d-4e37-ad33-de92033021a8 stroke:#2c3143,stroke-width:4px;
  15["Monocle3 learnGraph"];
  6 -->|output_rds| 15;
  ed2003aa-4680-409f-8d79-e79b878a786c["Output\nMonocle3 learnGraph on input dataset(s): cds3"];
  15 --> ed2003aa-4680-409f-8d79-e79b878a786c;
  style ed2003aa-4680-409f-8d79-e79b878a786c stroke:#2c3143,stroke-width:4px;
  16["Plot learned trajectory"];
  15 -->|output_rds| 16;
  6fa555f1-b4f2-4e5d-bce1-ed462d8e056d["Output\nCell types & learned trajectory path plot"];
  16 --> 6fa555f1-b4f2-4e5d-bce1-ed462d8e056d;
  style 6fa555f1-b4f2-4e5d-bce1-ed462d8e056d stroke:#2c3143,stroke-width:4px;
  17["Monocle3 orderCells"];
  15 -->|output_rds| 17;
  96d10412-3d7f-4970-b541-6f4367fa3f37["Output\nMonocle3 orderCells on input dataset(s): cds3"];
  17 --> 96d10412-3d7f-4970-b541-6f4367fa3f37;
  style 96d10412-3d7f-4970-b541-6f4367fa3f37 stroke:#2c3143,stroke-width:4px;
  18["Monocle3 diffExp"];
  17 -->|output_rds| 18;
  db1dc457-2d6e-47cc-b7ce-d0a4d23e9498["Output\nDifferential expression of genes - table"];
  18 --> db1dc457-2d6e-47cc-b7ce-d0a4d23e9498;
  style db1dc457-2d6e-47cc-b7ce-d0a4d23e9498 stroke:#2c3143,stroke-width:4px;
  19["Plot pseudotime"];
  17 -->|output_rds| 19;
  d1b3efd2-0a81-4dad-8652-589c2678fbaa["Output\nPseudotime plot"];
  19 --> d1b3efd2-0a81-4dad-8652-589c2678fbaa;
  style d1b3efd2-0a81-4dad-8652-589c2678fbaa stroke:#2c3143,stroke-width:4px;

Trajectory analysis using Monocle3 - full tutorial workflow

Julia Jakiela

Last updated May 16, 2023

Launch in Tutorial Mode question
License: CC-BY-4.0
Tests: ✅ Results: Not yet automated

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;

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:

Video: Importing a workflow from URL