Unit

UNIT 13.12 Census for Proteome Quantification

  1. Sung Kyu Park,
  2. John R. Yates III

Published Online: 1 MAR 2010

DOI: 10.1002/0471250953.bi1312s29

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Park, S. K. and Yates, J. R. 2010. Census for Proteome Quantification. Current Protocols in Bioinformatics. 29:13.12:13.12.1–13.12.11.

Author Information

  1. The Scripps Research Institute, La Jolla, California

Publication History

  1. Published Online: 1 MAR 2010
  2. Published Print: MAR 2010

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., 15N, 18O, 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. Curr. Protoc. Bioinform. 29:13.12.1-13.12.11. © 2010 by John Wiley & Sons, Inc.

Keywords:

  • Census;
  • mass spectrometry data;
  • proteomics data;
  • stable isotope label;
  • label-free analysis