TEST DATA for Enhanced protein isoform characterization through long-read proteogenomics
| Main Authors: | Miller, Rachel, Jordan, Ben, Mehlferber, Madison, Jeffery, Erin, Chatzipantsiou, Christina, Kaur, Simran, Millikin, Robert, Shortreed, Michael, TIberi, Simone, Conesa, Ana, Smith, Lloyd, Deslattes Mays, Anne, Sheynkman, Gloria |
|---|---|
| Format: | info dataset Journal |
| Terbitan: |
, 2021
|
| Subjects: | |
| Online Access: |
https://zenodo.org/record/5234651 |
Daftar Isi:
- Test data for The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g. PacBio, Oxford Nanopore) provides full-length transcript sequencing, which can be used to predict full-length proteins. Here, we describe a long-read proteogenomics approach for integrating matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discover novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data in protein inference to enable detection of protein isoforms that are intractable to MS detection. We have released an open-source Nextflow pipeline that integrates long-read sequencing in a proteomic workflow for isoform-resolved analysis. Companion Repositories: Long-Read-Proteogenomics Workflow GitHub Repository Release Long-Read-Proteogenomics Analysis GitHub Repository Release Companion Datasets Jurkat Samples and Reference Data Long-Read-Proteogenomics Workflow Results using Jurkat Sample data This Repository contains the test data, specifically: TEST Data for Long-Read-Proteogenomics Workflow GitHub Actions