Improving Identification of Differentially Expressed Genes in Microarray Studies Using Information From Public Databases

Abstract

Summary: The process of identifying differentially expressed genes in miroarray studies with small sample sizes can be improved substantially by extracting information from a large number of datasets accumulated in public databases. Abstract: We demonstrate that the process of identifying differentially expressed genes in microarray studies with small sample sizes can be substantially improved by extracting information from a large number of datasets accumulated in public databases. The improvement comes from more reliable estimates of gene-specific variances based on other datasets. For a two-group comparison with two arrays in each group, for example, the result of our method was comparable to that of a t-test analysis with five samples in each group or to that of a regularized t-test analysis with three samples in each group. Our results are further improved by weighting the results of our approach with the regularized t-test results in a hybrid method.