Census for proteome quantification.

Abstract

Quantitative analysis has become increasingly important in the proteomics field; however, the large amount of mass spectrometric data and the different types of quantitative strategies make data analysis ever challenging. Here we describe a quantitative software tool called Census to analyze high-throughput mass spectrometry data from shotgun proteomics experiments in an efficient way. Census is capable of analyzing various stable isotope labeling experiments (using, e.g., (15)N, (18)O, SILAC, iTRAQ, TMT) in addition to labeling-free experiments. With high-resolution data, Census increases the quantitative accuracy by minimizing the contributions of interfering peaks and chemical noise with a small accuracy tolerance for each isotope peak. Census provides various scoring algorithms including least-squares correlation, weight average, singleton peptide detection with discriminant analysis, and probability score for each peptide. Furthermore, Census has built-in multiple statistical filters to maintain robust quality control on quantitative results.