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

Bas van Breukelen | Zendy; Henk W. P. van den Toorn | Zendy; Mădălina M. Drugan | Zendy; Albert J. R. Heck | Zendy

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

Author(s) -

Bas van Breukelen,

Henk W. P. van den Toorn,

Mădălina M. Drugan,

Albert J. R. Heck

Publication year - 2009

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btp181

Subject(s) - computer science , toolbox , software , quantitative proteomics , data mining , source code , mass spectrometry , filter (signal processing) , set (abstract data type) , data set , proteomics , chemistry , chromatography , programming language , artificial intelligence , computer vision , gene , biochemistry

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 refine 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.

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