Filter, Plot and Explore Single-cell RNA-seq Data updated

single-cell-scrna-case_basic-pipeline/filter--plot-and-explore-single-cell-rna-seq-data-updated

Author(s)
Wendi Bacon, Julia Jakiela
version Version
1
last_modification Last updated
Jun 13, 2023
license License
CC-BY-4.0
galaxy-tags Tags
transcriptomics

Features

Tutorial
hands_on Filter, plot and explore single-cell RNA-seq data with Scanpy
workflow Other workflows associated with this material
Workflow Testing
Tests: ✅
Results: Not yet automated
FAIRness purl PURL
https://gxy.io/GTN:W00197
RO-Crate logo with flask Download Workflow RO-Crate Workflowhub cloud with gears logo View on WorkflowHub
Launch in Tutorial Mode question
galaxy-download Download
flowchart TD
  0["ℹ️ Input Dataset\nMito-counted AnnData"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["Inspect AnnData"];
  0 -->|output| 1;
  2["Scanpy FilterCells"];
  0 -->|output| 2;
  6a00b14b-d3f8-4771-963a-76115c8eaf2f["Output\nGenes-filtered Object"];
  2 --> 6a00b14b-d3f8-4771-963a-76115c8eaf2f;
  style 6a00b14b-d3f8-4771-963a-76115c8eaf2f stroke:#2c3143,stroke-width:4px;
  3["Plot"];
  0 -->|output| 3;
  c123842e-b2d2-43ad-81f0-6ba3b45d4021["Output\nScatter - genes x UMIs"];
  3 --> c123842e-b2d2-43ad-81f0-6ba3b45d4021;
  style c123842e-b2d2-43ad-81f0-6ba3b45d4021 stroke:#2c3143,stroke-width:4px;
  4["Plot"];
  0 -->|output| 4;
  f1020d4d-555e-42fa-ba21-52a151b91a5b["Output\nScatter - mito x genes"];
  4 --> f1020d4d-555e-42fa-ba21-52a151b91a5b;
  style f1020d4d-555e-42fa-ba21-52a151b91a5b stroke:#2c3143,stroke-width:4px;
  5["Plot"];
  0 -->|output| 5;
  a7fe6020-8f1e-470a-9ed3-f2b5e95516e0["Output\nViolin - genotype - log"];
  5 --> a7fe6020-8f1e-470a-9ed3-f2b5e95516e0;
  style a7fe6020-8f1e-470a-9ed3-f2b5e95516e0 stroke:#2c3143,stroke-width:4px;
  6["Plot"];
  0 -->|output| 6;
  15e501bc-8ddb-4519-89eb-dde431ea96c1["Output\nViolin - batch - log"];
  6 --> 15e501bc-8ddb-4519-89eb-dde431ea96c1;
  style 15e501bc-8ddb-4519-89eb-dde431ea96c1 stroke:#2c3143,stroke-width:4px;
  7["Inspect AnnData"];
  0 -->|output| 7;
  8["Plot"];
  0 -->|output| 8;
  eff22f46-baa6-4e00-ba82-d5e12ce26ff0["Output\nScatter - mito x UMIs"];
  8 --> eff22f46-baa6-4e00-ba82-d5e12ce26ff0;
  style eff22f46-baa6-4e00-ba82-d5e12ce26ff0 stroke:#2c3143,stroke-width:4px;
  9["Inspect AnnData"];
  0 -->|output| 9;
  10["Plot"];
  0 -->|output| 10;
  56677ca4-129c-476c-85ec-69d1bb3d800d["Output\nViolin - sex - log"];
  10 --> 56677ca4-129c-476c-85ec-69d1bb3d800d;
  style 56677ca4-129c-476c-85ec-69d1bb3d800d stroke:#2c3143,stroke-width:4px;
  11["Plot"];
  2 -->|output_h5ad| 11;
  acb61ea4-bcb9-45db-beef-e2bf1a176701["Output\nViolin - Filterbygenes"];
  11 --> acb61ea4-bcb9-45db-beef-e2bf1a176701;
  style acb61ea4-bcb9-45db-beef-e2bf1a176701 stroke:#2c3143,stroke-width:4px;
  12["Scanpy FilterCells"];
  2 -->|output_h5ad| 12;
  51853662-4519-4229-a2ea-b22a53e7ef73["Output\nCounts-filtered Object"];
  12 --> 51853662-4519-4229-a2ea-b22a53e7ef73;
  style 51853662-4519-4229-a2ea-b22a53e7ef73 stroke:#2c3143,stroke-width:4px;
  13["Inspect AnnData"];
  2 -->|output_h5ad| 13;
  362a7fe6-24bb-4398-ae48-870f4b4bb774["Output\nGeneral - Filterbygenes"];
  13 --> 362a7fe6-24bb-4398-ae48-870f4b4bb774;
  style 362a7fe6-24bb-4398-ae48-870f4b4bb774 stroke:#2c3143,stroke-width:4px;
  14["Inspect AnnData"];
  12 -->|output_h5ad| 14;
  edf24149-9341-4fe7-b10c-3fcf092faaa5["Output\nGeneral - Filterbycounts"];
  14 --> edf24149-9341-4fe7-b10c-3fcf092faaa5;
  style edf24149-9341-4fe7-b10c-3fcf092faaa5 stroke:#2c3143,stroke-width:4px;
  15["Scanpy FilterCells"];
  12 -->|output_h5ad| 15;
  a88ec405-265f-4a59-a75e-34e3b05b0096["Output\nMito-filtered Object"];
  15 --> a88ec405-265f-4a59-a75e-34e3b05b0096;
  style a88ec405-265f-4a59-a75e-34e3b05b0096 stroke:#2c3143,stroke-width:4px;
  16["Plot"];
  12 -->|output_h5ad| 16;
  a7c8b0d9-82d3-4438-a212-b5f7c56d36b8["Output\nViolin - Filterbycounts"];
  16 --> a7c8b0d9-82d3-4438-a212-b5f7c56d36b8;
  style a7c8b0d9-82d3-4438-a212-b5f7c56d36b8 stroke:#2c3143,stroke-width:4px;
  17["Inspect AnnData"];
  15 -->|output_h5ad| 17;
  56882809-e19f-451a-8010-bc55dcee482f["Output\nGeneral - Filterbymito"];
  17 --> 56882809-e19f-451a-8010-bc55dcee482f;
  style 56882809-e19f-451a-8010-bc55dcee482f stroke:#2c3143,stroke-width:4px;
  18["Scanpy FilterGenes"];
  15 -->|output_h5ad| 18;
  00846477-dec5-408a-83b2-105fff7ce05b["Output\nFiltered Object"];
  18 --> 00846477-dec5-408a-83b2-105fff7ce05b;
  style 00846477-dec5-408a-83b2-105fff7ce05b stroke:#2c3143,stroke-width:4px;
  19["Plot"];
  15 -->|output_h5ad| 19;
  7582e113-2004-4255-a1f3-d3123373f342["Output\nViolin - Filterbymito"];
  19 --> 7582e113-2004-4255-a1f3-d3123373f342;
  style 7582e113-2004-4255-a1f3-d3123373f342 stroke:#2c3143,stroke-width:4px;
  20["Inspect AnnData"];
  18 -->|output_h5ad| 20;
  2d870a40-c602-4a1c-afef-450489354d39["Output\nGeneral - Filtered object"];
  20 --> 2d870a40-c602-4a1c-afef-450489354d39;
  style 2d870a40-c602-4a1c-afef-450489354d39 stroke:#2c3143,stroke-width:4px;
  21["Scanpy NormaliseData"];
  18 -->|output_h5ad| 21;
  22["Scanpy FindVariableGenes"];
  21 -->|output_h5ad| 22;
  a0eb92b1-0263-4179-b7af-4bd9bcc9c960["Output\nUse_me_FVG"];
  22 --> a0eb92b1-0263-4179-b7af-4bd9bcc9c960;
  style a0eb92b1-0263-4179-b7af-4bd9bcc9c960 stroke:#2c3143,stroke-width:4px;
  23["Scanpy ScaleData"];
  22 -->|output_h5ad| 23;
  5776dbb9-0cac-40c0-9bae-9accae16a7a0["Output\nUse_me_Scaled"];
  23 --> 5776dbb9-0cac-40c0-9bae-9accae16a7a0;
  style 5776dbb9-0cac-40c0-9bae-9accae16a7a0 stroke:#2c3143,stroke-width:4px;
  24["Scanpy RunPCA"];
  23 -->|output_h5ad| 24;
  25["Plot"];
  24 -->|output_h5ad| 25;
  f0b6f578-050f-4936-9ee7-9956b0760c6f["Output\nPCA Variance"];
  25 --> f0b6f578-050f-4936-9ee7-9956b0760c6f;
  style f0b6f578-050f-4936-9ee7-9956b0760c6f stroke:#2c3143,stroke-width:4px;
  26["Scanpy ComputeGraph"];
  24 -->|output_h5ad| 26;
  27["Scanpy RunTSNE"];
  26 -->|output_h5ad| 27;
  28["Scanpy RunUMAP"];
  27 -->|output_h5ad| 28;
  29["Scanpy FindCluster"];
  28 -->|output_h5ad| 29;
  30["Scanpy FindMarkers"];
  29 -->|output_h5ad| 30;
  7cfe5c9c-1c80-41b4-b669-633b1d7d40e3["Output\nMarkers - cluster"];
  30 --> 7cfe5c9c-1c80-41b4-b669-633b1d7d40e3;
  style 7cfe5c9c-1c80-41b4-b669-633b1d7d40e3 stroke:#2c3143,stroke-width:4px;
  98e98405-951e-4c6c-be01-3c925ae35449["Output\nFinal object"];
  30 --> 98e98405-951e-4c6c-be01-3c925ae35449;
  style 98e98405-951e-4c6c-be01-3c925ae35449 stroke:#2c3143,stroke-width:4px;
  31["Scanpy FindMarkers"];
  29 -->|output_h5ad| 31;
  1e9f229d-eb34-4a5b-a6d9-e70c7b0581f4["Output\nMarkers - genotype"];
  31 --> 1e9f229d-eb34-4a5b-a6d9-e70c7b0581f4;
  style 1e9f229d-eb34-4a5b-a6d9-e70c7b0581f4 stroke:#2c3143,stroke-width:4px;
  32["Scanpy PlotEmbed"];
  30 -->|output_h5ad| 32;
  33["Scanpy PlotEmbed"];
  30 -->|output_h5ad| 33;
  34["Manipulate AnnData"];
  30 -->|output_h5ad| 34;
  35["Scanpy PlotEmbed"];
  30 -->|output_h5ad| 35;
  36["Inspect AnnData"];
  30 -->|output_h5ad| 36;
  37["AnnData Operations"];
  34 -->|anndata| 37;
  30 -->|output_h5ad| 37;
  38["Join two Datasets"];
  30 -->|output_tsv| 38;
  36 -->|var| 38;
  39["Join two Datasets"];
  31 -->|output_tsv| 39;
  36 -->|var| 39;
  40["AnnData Operations"];
  37 -->|output_h5ad| 40;
  10bd70f8-ffcb-442b-9647-e5b947b6d35e["Output\nFinal cell annotated object"];
  40 --> 10bd70f8-ffcb-442b-9647-e5b947b6d35e;
  style 10bd70f8-ffcb-442b-9647-e5b947b6d35e stroke:#2c3143,stroke-width:4px;
  41["Cut"];
  38 -->|out_file1| 41;
  4f822c1c-91c5-4be4-8f9b-d5bdda0a037e["Output\nMarkers - cluster - named"];
  41 --> 4f822c1c-91c5-4be4-8f9b-d5bdda0a037e;
  style 4f822c1c-91c5-4be4-8f9b-d5bdda0a037e stroke:#2c3143,stroke-width:4px;
  42["Cut"];
  39 -->|out_file1| 42;
  3b471f3d-263d-4299-9b7d-8a8ae1aa556e["Output\nMarkers - genotype - named"];
  42 --> 3b471f3d-263d-4299-9b7d-8a8ae1aa556e;
  style 3b471f3d-263d-4299-9b7d-8a8ae1aa556e stroke:#2c3143,stroke-width:4px;
  43["Scanpy PlotEmbed"];
  40 -->|output_h5ad| 43;

Inputs

Input Label
Input dataset Mito-counted AnnData

Outputs

From Output Label
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9 Scanpy FilterCells
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9 Scanpy FilterCells
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9 Scanpy FilterCells
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_genes/scanpy_filter_genes/1.8.1+galaxy9 Scanpy FilterGenes
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_normalise_data/scanpy_normalise_data/1.8.1+galaxy9 Scanpy NormaliseData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_find_variable_genes/scanpy_find_variable_genes/1.8.1+galaxy9 Scanpy FindVariableGenes
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_scale_data/scanpy_scale_data/1.8.1+galaxy9 Scanpy ScaleData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_run_pca/scanpy_run_pca/1.8.1+galaxy9 Scanpy RunPCA
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 Plot
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_compute_graph/scanpy_compute_graph/1.8.1+galaxy9 Scanpy ComputeGraph
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_run_tsne/scanpy_run_tsne/1.8.1+galaxy9 Scanpy RunTSNE
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_run_umap/scanpy_run_umap/1.8.1+galaxy9 Scanpy RunUMAP
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_find_cluster/scanpy_find_cluster/1.8.1+galaxy9 Scanpy FindCluster
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_find_markers/scanpy_find_markers/1.8.1+galaxy9 Scanpy FindMarkers
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_find_markers/scanpy_find_markers/1.8.1+galaxy9 Scanpy FindMarkers
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9 Scanpy PlotEmbed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9 Scanpy PlotEmbed
toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1 Manipulate AnnData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9 Scanpy PlotEmbed
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 Inspect AnnData
toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy91 AnnData Operations
join1 Join two Datasets
join1 Join two Datasets
toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy91 AnnData Operations
Cut1 Cut
Cut1 Cut
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9 Scanpy PlotEmbed

Tools

Tool Links
Cut1
join1
toolshed.g2.bx.psu.edu/repos/ebi-gxa/anndata_ops/anndata_ops/1.8.1+galaxy91 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_compute_graph/scanpy_compute_graph/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_cells/scanpy_filter_cells/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_filter_genes/scanpy_filter_genes/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_find_cluster/scanpy_find_cluster/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_find_markers/scanpy_find_markers/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_find_variable_genes/scanpy_find_variable_genes/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_normalise_data/scanpy_normalise_data/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_plot_embed/scanpy_plot_embed/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_run_pca/scanpy_run_pca/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_run_tsne/scanpy_run_tsne/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_run_umap/scanpy_run_umap/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_scale_data/scanpy_scale_data/1.8.1+galaxy9 View in ToolShed
toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/iuc/anndata_manipulate/anndata_manipulate/0.7.5+galaxy1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/iuc/scanpy_plot/scanpy_plot/1.7.1+galaxy1 View in ToolShed

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:

Video: Importing a workflow from URL

Version History

Version Commit Time Comments
1 9a3fc8a6d 2023-06-09 21:11:27 new workflow tests

For Admins

Installing the workflow tools

wget https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-case_basic-pipeline/workflows/Filter,-Plot-and-Explore-Single-cell-RNA-seq-Data-updated.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