Processing of Data Generated by 2-Dimensional Gel Electrophoresis for Statistical Analysis: Missing Data, Normalization, and Statistics

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Abstract
Several high-throughput statistical methods were evaluated for processing data generated by two-dimensional polyacrylamide gel electrophoresis, including how to handle missing data, normalization, and statistical analysis of data obtained from 2-D gels. Quantile normalization combined with a nonparametric permutation test based on minimizing false discover rates gave the highest yield of proteins that changed with genotype and detected the anticipated 50% decrease in Mn-superoxide dismutase (MnSOD) protein levels in mitochondrial extracts obtained from MnSOD-deficient mice. Keywords: 2-D PAGE • missing data • normalization • mitochondria • permutation test • false discovery rates