Increased power for the analysis of label-free LC-MS/MS proteomics data by combining spectral counts and peptide peak attributes.

ABSTRACT: Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics provides a wealth of information about proteins present in biological samples. In bottom-up LC-MS/MS-based proteomics, proteins are enzymatically digested into peptides prior to query by LC-MS/MS. Thus, the information directly available from the LC-MS/MS data is at the peptide level. If a protein-level analysis is desired, the peptide-level information must be rolled up into protein-level information. We propose a principal component analysis-based statistical method, ProPCA, for efficiently estimating relative protein abundance from bottom-up label-free LC-MS/MS data that incorporates both spectral count information and LC-MS peptide ion peak attributes, such as peak area, volume, or height. ProPCA may be used eff

SUBMITTER: Dicker L 

PROVIDER: S-EPMC3101957 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature