Modeling biological variability in 2-D gel proteomic carcinogenesis experiments.
We propose a statistical method to model the underlying distribution of protein spot volumes in 2-D gels using a generalized model (GM). We apply this approach to discover mechanisms of chemical carcinogenesis in a rodent model. We generated 247 protein spots that were common to all gels (n = 18). Traditional statistical methods found 6.5% (13 out of 247) significant protein spots, our GM approach yielded a total of 53 (22.5%) differentially expressed protein spots.
Rowell
Craig
C
Department of Pharmacology and Toxicology, UAB Comprehensive Cancer, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
Carpenter
Mark
M
Lamartiniere
Coral A
CA
D015127:9,10-Dimethyl-1,2-benzanthracene; D000818:Animals; D015415:Biomarkers / Q000737:chemistry; D002273:Carcinogens; D002471:Cell Transformation, Neoplastic; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods*; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D023281:Genomics; D015674:Mammary Neoplasms, Animal; D015233:Models, Statistical; D009369:Neoplasms / Q000378:metabolism; D010865:Pilot Projects; D040901:Proteomics / Q000379:methods*; D051381:Rats; D017207:Rats, Sprague-Dawley; D015398:Signal Transduction
D015415:Biomarkers; D002273:Carcinogens; D015127:9,10-Dimethyl-1,2-benzanthracene