A statistical model for iTRAQ data analysis.
We describe biological and experimental factors that induce variability in reporter ion peak areas obtained from iTRAQ experiments. We demonstrate how these factors can be incorporated into a statistical model for use in evaluating differential protein expression and highlight the benefits of using analysis of variance to quantify fold change. We demonstrate the model's utility based on an analysis of iTRAQ data derived from a spike-in study.
Hill
Elizabeth G
EG
Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. hille@musc.edu
Schwacke
John H
JH
Comte-Walters
Susana
S
Slate
Elizabeth H
EH
Oberg
Ann L
AL
Eckel-Passow
Jeanette E
JE
Therneau
Terry M
TM
Schey
Kevin L
KL
D000595:Amino Acid Sequence; D000704:Analysis of Variance; D002364:Caseins / Q000032:analysis; D002851:Chromatography, High Pressure Liquid; D004798:Enzymes / Q000032:analysis; D020869:Gene Expression Profiling; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods; D015233:Models, Statistical; D008969:Molecular Sequence Data; D014176:Protein Biosynthesis; D017510:Protein Folding; D011506:Proteins / Q000032:analysis*; D012710:Serum Albumin, Bovine / Q000032:analysis; D012984:Software
D002364:Caseins; D004798:Enzymes; D011506:Proteins; D012710:Serum Albumin, Bovine