title: Improving identification of differentially expressed genes in microarray studies using information from 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.
authors.affiliation: Harvard-Partners Center for Genetics and Genomics, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
authors.forename: Richard D
authors.initials: RD
authors.lastname: Kim
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Park
mesh_terms: D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods* / Q000706:statistics & numerical data; D005786:Gene Expression Regulation / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000706:statistics & numerical data