Biological validation of differentially expressed genes in chronic lymphocytic leukemia identified by applying multiple statistical methods to oligonucleotide microarrays.

ABSTRACT: Oligonucleotide microarrays are a powerful tool for profiling the expression levels of thousands of genes. Different statistical methods for identifying differentially expressed genes can yield different results. To our knowledge, no experimental test has been performed to decide which method best identifies genes that are truly differentially expressed. We applied three statistical methods (dChip, t-test on log-transformed data, and Wilcoxon test) to identify differentially expressed genes in previously untreated patients with chronic lymphocytic leukemia (CLL). We used a training set of Affymetrix Hu133A microarray data from 11 patients with unmutated immunoglobulin (Ig) heavy chain variable region (VH) genes and 8 patients with mutated Ig VH genes. Differential expression was validated

SUBMITTER: Abruzzo LV 

PROVIDER: S-EPMC1867538 | biostudies-literature | 2005 Aug

REPOSITORIES: biostudies-literature