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Post alignment clustering procedure for comparative quantitative proteomics LC‐MS Data
Author(s) -
de Groot Joost C. W.,
Fiers Mark W. E. J.,
van Ham Roeland C. H. J.,
America Antoine H. P.
Publication year - 2007
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200700707
Subject(s) - cluster analysis , software , matching (statistics) , computer science , data mining , cluster (spacecraft) , proteomics , chromatography , pattern recognition (psychology) , artificial intelligence , chemistry , mathematics , statistics , biochemistry , gene , programming language
Abstract Comparative LC‐MS is a powerful method for detailed quantitative comparison of complex protein mixtures. Dedicated software is required for detection, matching, and alignment of peaks in multiple LC‐MS datasets. However, retention time shifts, saturation effects, limitations of experimental accuracy, and possible occurrence of split peaks make it difficult for software to perfectly match all chromatograms. We describe a procedure to assess the above problems and show that dataset quality can be enhanced with the aid of cluster analysis.