APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control.

ABSTRACT: Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate (FDR). To fill in this gap, we proposed a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, u

SUBMITTER: Chen YE 

PROVIDER: S-EPMC12536914 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature