Abstract：
:Mass spectrometry (MS) has become an accessible tool for whole proteome quantitation with the ability to characterize protein expression across thousands of proteins within a single experiment. A subset of MS quantification methods (e.g., SILAC and label-free) monitor the relative intensity of intact peptides, where thousands of measurements can be made from a single mass spectrum. An alternative approach, isobaric labeling, enables precise quantification of multiple samples simultaneously through unique and sample specific mass reporter ions. Consequently, in a single scan, the quantitative signal comes from a limited number of spectral features (≤11). The signal observed for these features is constrained by automatic gain control, forcing codependence of concurrent signals. The study of constrained outcomes primarily belongs to the field of compositional data analysis. We show experimentally that isobaric tag proteomics data are inherently compositional and highlight the implications for data analysis and interpretation. We present a new statistical model and accompanying software that improves estimation accuracy and the ability to detect changes in protein abundance. Finally, we demonstrate a unique compositional effect on proteins with infinite changes. We conclude that many infinite changes will appear small and that the magnitude of these estimates is highly dependent on experimental design.
journal_name
J Proteome Resjournal_title
Journal of proteome researchauthors
O'Brien JJ,O'Connell JD,Paulo JA,Thakurta S,Rose CM,Weekes MP,Huttlin EL,Gygi SPdoi
10.1021/acs.jproteome.7b00699subject
Has Abstractpub_date
2018-01-05 00:00:00pages
590-599issue
1eissn
1535-3893issn
1535-3907journal_volume
17pub_type
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