MuSiC-Deconvolution: Data generation | sc | matrix + ESet 1.0
Visit source
Download RO-Crate
Run on GalaxyThis workflow creates an ESet object from scRNA metadata file and EBI SCXA retrieveal
Associated Tutorial
This workflows is part of the tutorial Matrix Exchange Format to ESet | Creating a single-cell RNA-seq reference dataset for deconvolution, available in the GTN
Features
- Uses subworkflows
Thanks to...
Workflow Author(s): Wendi Bacon, Mehmet Tekman
Tutorial Author(s): Wendi Bacon, Mehmet Tekman
Tutorial Contributor(s): Marisa Loach, Mehmet Tekman, Saskia Hiltemann, Wendi Bacon, Helena Rasche, Pablo Moreno, Julia Jakiela, Pavankumar Videm
Inputs
| ID | Name | Description | Type |
|---|---|---|---|
| Single cell metadata | Single cell metadata | This should be output from the MuSiC Deconvolution | Data generation | sc | metadata workflow |
|
Steps
| ID | Name | Description |
|---|---|---|
| 0 | EBI SCXA Data Retrieval | toolshed.g2.bx.psu.edu/repos/ebi-gxa/retrieve_scxa/retrieve_scxa/v0.0.2+galaxy2 |
| 2 | Scanpy Read10x | toolshed.g2.bx.psu.edu/repos/ebi-gxa/scanpy_read_10x/scanpy_read_10x/1.8.1+galaxy0 |
| 3 | Inspect AnnData | toolshed.g2.bx.psu.edu/repos/iuc/anndata_inspect/anndata_inspect/0.7.5+galaxy1 |
| 4 | Transpose | toolshed.g2.bx.psu.edu/repos/iuc/datamash_transpose/datamash_transpose/1.1.0+galaxy2 |
| 5 | annotateMyIDs | toolshed.g2.bx.psu.edu/repos/iuc/annotatemyids/annotatemyids/3.14.0+galaxy1 |
| 6 | 1st step removed - Convert from Ensembl to GeneSymbol, summing duplicate genes | 171553 |
| 7 | Construct Expression Set Object | toolshed.g2.bx.psu.edu/repos/bgruening/music_construct_eset/music_construct_eset/0.1.1+galaxy4 |
| 8 | Manipulate Expression Set Object | toolshed.g2.bx.psu.edu/repos/bgruening/music_manipulate_eset/music_manipulate_eset/0.1.1+galaxy4 |
| 9 | Manipulate Expression Set Object | toolshed.g2.bx.psu.edu/repos/bgruening/music_manipulate_eset/music_manipulate_eset/0.1.1+galaxy4 |
Outputs
| ID | Name | Description | Type |
|---|---|---|---|
| _anonymous_output_1 | _anonymous_output_1 | n/a |
|
| _anonymous_output_2 | _anonymous_output_2 | n/a |
|
| _anonymous_output_3 | _anonymous_output_3 | n/a |
|
| _anonymous_output_4 | _anonymous_output_4 | n/a |
|
| Scanpy Read10x on input dataset(s): anndata | Scanpy Read10x on input dataset(s): anndata | n/a |
|
| _anonymous_output_5 | _anonymous_output_5 | n/a |
|
| _anonymous_output_6 | _anonymous_output_6 | n/a |
|
| annotateMyIDs on input dataset(s): Annotated IDs | annotateMyIDs on input dataset(s): Annotated IDs | n/a |
|
| _anonymous_output_7 | _anonymous_output_7 | n/a |
|
| _anonymous_output_8 | _anonymous_output_8 | n/a |
|
| Construct Expression Set Object on input dataset(s): RData ESet Object | Construct Expression Set Object on input dataset(s): RData ESet Object | n/a |
|
| Construct Expression Set Object on input dataset(s): General Info | Construct Expression Set Object on input dataset(s): General Info | n/a |
|
| Manipulate Expression Set Object on input dataset(s): ExpressionSet Object | Manipulate Expression Set Object on input dataset(s): ExpressionSet Object | n/a |
|
| _anonymous_output_9 | _anonymous_output_9 | n/a |
|
Version History
master
Creators and Submitter
Views: 258 Downloads: 36 Runs: 0
Created: 2nd Jun 2025 at 10:58
AttributionsNone
Related items
Teams: Galaxy Training Network
Organizations: Galaxy
I'm a bot managed by @hexylena to upload workflows from the Galaxy Training Network to the WorkflowHub. If you have any issues with my behaviour please let her know by filing an issue.
Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational biological research.
- Accessible: Users can easily run tools without writing code or using the CLI; all via a user-friendly web interface.
- Reproducible: Galaxy captures all the metadata from an analysis, making it completely reproducible.
- Transparent: Users share and publish analyses via interactive pages that can enhance analyses with user annotations.
- Scalable: Galaxy can run ...
Teams: Galaxy Training Network
Web page: https://galaxyproject.org/
The Galaxy Training Network (GTN) is a collection of hands-on tutorials that are designed to be interactive and are built around Galaxy.
These tutorials can be used for learning and teaching how to use Galaxy for general data analysis, as well as a wide array of hands-on tutorials covering specific domains such as assembly, RNA-Seq analysis, deep learning, climate analysis, and more!
