Triqler for Protein Summarization of Data from Data-Independent Acquisition Mass Spectrometry.

ABSTRACT: A frequent goal, or subgoal, when processing data from a quantitative shotgun proteomics experiment is a list of proteins that are differentially abundant under the examined experimental conditions. Unfortunately, obtaining such a list is a challenging process, as the mass spectrometer analyzes the proteolytic peptides of a protein rather than the proteins themselves. We have previously designed a Bayesian hierarchical probabilistic model, Triqler, for combining peptide identification and quantification errors into probabilities of proteins being differentially abundant. However, the model was developed for data from data-dependent acquisition. Here, we show that Triqler is also compatible with data-independent acquisition data after applying minor alterations for the missing value distrib

SUBMITTER: Truong P 

PROVIDER: S-EPMC10088044 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature