Improved data normalization methods for reverse phase protein microarray analysis of complex biological samples.

ABSTRACT: Reverse phase protein microarrays (RPMA) are designed for quantitative, multiplexed analysis of proteins, and their posttranslational modified forms, from a limited amount of sample. To correct for sample to sample variability due to the number of cells in each lysate and the presence of extracellular proteins or red blood cells, a normalization method is required that is independent of these potentially confounding parameters. We adopted a gene microarray algorithm for use with RPMA to optimize the proteomic data normalization process and developed a systematic approach to RPMA processing and analysis, tailored to the study set. Our approach capitalizes on the gene microarray algorithms geNorm and NormFinder to identify the normalization parameter with the lowest variability across a prot

SUBMITTER: Chiechi A 

PROVIDER: S-EPMC3771668 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature