Census for Proteome Quantification

Sung Kyu Park1, John R. Yates1

1 The Scripps Research Institute, La Jolla, California
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 13.12
DOI:  10.1002/0471250953.bi1312s29
Online Posting Date:  March, 2010
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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

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Table of Contents

  • Introduction
  • Basic Protocol 1: Using Census to Quantitatively Analyze Proteomic Data
  • Support Protocol 1: Downloading and Installing Census
  • Guidelines for Understanding Results
  • Commentary
  • Literature Cited
  • Figures
  • Tables
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Literature Cited

Literature Cited
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