StatQuant: a post-quantification analysis toolbox for improving quantitative mass spectrometry

被引：30
作者：
van Breukelen, Bas [1 ,2 ,3 ,4 ,5 ,6 ]
van den Toorn, Henk W. P. [1 ,2 ,3 ,4 ,5 ,6 ]
Drugan, Madalina M. [1 ,2 ,3 ,4 ,5 ,6 ]
Heck, Albert J. R. [1 ,2 ,3 ,4 ,5 ,6 ]
机构：
[1] Univ Utrecht, Biomol Mass Spectrometry & Prote Grp, NL-3584 CH Utrecht, Netherlands
[2] Univ Utrecht, Bijvoet Ctr Biomol Res, NL-3584 CH Utrecht, Netherlands
[3] Univ Utrecht, Utrecht Inst Pharmaceut Sci, NL-3584 CH Utrecht, Netherlands
[4] Netherlands Prote Ctr, NL-3584 CH Utrecht, Netherlands
[5] Netherlands Bioinformat Ctr, NL-6525 GA Nijmegen, Netherlands
[6] Ctr Biomed Genet, NL-3584 CH Utrecht, Netherlands
来源：
BIOINFORMATICS | 2009年 / 25卷 / 11期
关键词：
CELL-CULTURE; AMINO-ACIDS; PROTEOMICS; SILAC; ARGININE;
D O I：
10.1093/bioinformatics/btp181
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
Motivation: Mass spectrometric protein quantitation has emerged as a high-throughput tool to yield large amounts of data on peptide and protein abundances. Currently, differential abundance data can be calculated from peptide intensity ratios by several automated quantitation software packages available. There is, however, still a great need for additional processing to validate and re. ne the quantitation results. Here, we present a software tool, termed StatQuant, that offers a set of statistical tools to process, filter, compare and represent data from several quantitative proteomics software packages such as MSQuant. StatQuant offers the researcher post-processing methods to achieve improved confidence on the obtained protein ratios.
引用
收藏
页码：1472 / 1473
页数：2
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