aGOtool
aGOtool performs protein-abundance–aware Gene Ontology and UniProt keyword enrichment for post-translational modification (PTM) datasets to correct mass-spectrometry–based detection bias and reveal PTM-specific functional signals.
Key Features:
- Protein-abundance–aware enrichment: Performs GO and UniProt keyword enrichment that weights background term frequencies by protein abundance distributions.
- Statistical abundance correction: Implements a statistical correction that reweights GO-term frequencies according to protein abundance to reduce bias from highly expressed proteins.
- Proteome binning: Partitions the proteome into abundance bins and reweights GO-term associations in proportion to the frequency of modification in each bin.
- Abundance-corrected reference distribution: Generates an abundance-corrected reference distribution for enrichment testing.
- PTM type support: Supports analysis of multiple PTM types, including phosphorylation, ubiquitination, acetylation, and succinylation.
- Background comparisons: Enables comparisons of enrichment results across genome, observed proteome, and abundance-corrected backgrounds.
- Bias reduction and sensitivity: Reduces false enrichment driven by sampling bias in mass-spectrometry–based PTM identification and enhances detection of PTM-specific and under-represented functional categories.
Scientific Applications:
- PTM-specific functional inference: Distinguishing PTM-associated biological processes from artifacts of protein abundance in proteomics datasets.
- Comparative PTM analysis: Comparing enrichment across different PTM types and across genome, observed proteome, and abundance-corrected backgrounds to identify PTM-specific or shared functions.
- Reproducible PTM annotation: Supporting reproducible functional annotation of PTMs across diverse organisms and cell types.
Methodology:
Partitions the proteome into abundance bins, reweights GO-term associations proportional to the frequency of modification in each bin, and constructs an abundance-corrected reference distribution for enrichment analysis.
Topics
Collections
Details
- Tool Type:
- api
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Shell, Python
- Added:
- 9/3/2017
- Last Updated:
- 11/24/2024
Operations
Publications
Schölz C, Lyon D, Refsgaard JC, Jensen LJ, Choudhary C, Weinert BT. Avoiding abundance bias in the functional annotation of posttranslationally modified proteins. Nature Methods. 2015;12(11):1003-1004. doi:10.1038/nmeth.3621. PMID:26513550.
DOI: 10.1038/nmeth.3621
PMID: 26513550
Documentation
General
https://agotool.org/