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Heteromer score—using internal standards to assess the quality of proteomic data
Author(s) -
RogowskaWrzesinska Adelina,
Wrzesinski Krzysztof,
Fey Stephen J.
Publication year - 2014
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.201300457
Subject(s) - correlation coefficient , reproducibility , protein subunit , stoichiometry , data set , set (abstract data type) , correlation , quality (philosophy) , computer science , data mining , chemistry , analytical chemistry (journal) , chromatography , mathematics , artificial intelligence , biochemistry , machine learning , gene , physics , geometry , programming language , organic chemistry , quantum mechanics
In the cell, the majority of proteins exist in complexes. Most of these complexes have a constant stoichiometry and thus can be used as internal standards. In this rapid communication, we show that it is possible to calculate a correlation coefficient that reflects the reproducibility of the analytical approach used. The abundance of one subunit in a heterodimer is plotted against the abundance of the other, and this is repeated for all subunits in all heteromers found in the data set. The correlation coefficient obtained (the “heteromer score”) is a new bioinformatic tool that is independent of the method used to collect the data, requires no special sample preparation and can be used retrospectively on old datasets. It can be used for quality control, to indicate when a change becomes significant or identify complexes whose stoichiometry has been perturbed during the experiment.