'Proteome Annotation' 3.0
Visit source
Download RO-Crate
Run on GalaxyAnnotating a protein list identified by LC-MS/MS experiments
Associated Tutorial
This workflows is part of the tutorial Annotating a protein list identified by LC-MS/MS experiments, available in the GTN
Thanks to...
Tutorial Author(s): Valentin Loux, Florence Combes, David Christiany, Yves Vandenbrouck
Steps
| ID | Name | Description |
|---|---|---|
| 3 | Build tissue-specific expression dataset | toolshed.g2.bx.psu.edu/repos/proteore/proteore_tissue_specific_expression_data/retrieve_from_hpa/2019.02.27 |
| 4 | Filter by keywords and/or numerical value | toolshed.g2.bx.psu.edu/repos/proteore/proteore_filter_keywords_values/MQoutputfilter/2019.03.11 |
| 5 | ID Converter | toolshed.g2.bx.psu.edu/repos/proteore/proteore_id_converter/IDconverter/2019.03.07 |
| 6 | ID Converter | toolshed.g2.bx.psu.edu/repos/proteore/proteore_id_converter/IDconverter/2019.03.07 |
| 7 | Venn diagram | toolshed.g2.bx.psu.edu/repos/proteore/proteore_venn_diagram/Jvenn/2019.02.21 |
| 8 | Add expression data | toolshed.g2.bx.psu.edu/repos/proteore/proteore_expression_rnaseq_abbased/rna_abbased_data/2019.03.07 |
| 9 | Filter by keywords and/or numerical value | toolshed.g2.bx.psu.edu/repos/proteore/proteore_filter_keywords_values/MQoutputfilter/2019.03.11 |
| 10 | GO terms classification and enrichment analysis | toolshed.g2.bx.psu.edu/repos/proteore/proteore_clusterprofiler/cluter_profiler/2019.02.18 |
| 11 | Query pathway database | toolshed.g2.bx.psu.edu/repos/proteore/proteore_reactome/reactome_analysis/2019.03.05 |
Version History
master
Creators and Submitter
Views: 41 Downloads: 4 Runs: 0
Created: 2nd Jun 2025 at 10:52
Tags 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!
