Journal
BIOINFORMATICS
Volume 19, Issue 15, Pages 1945-1951Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btg264
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Motivation: In microarray studies gene discovery based on fold-change values is often misleading because error variability for each gene is heterogeneous under different biological conditions and intensity ranges. Several statistical testing methods for differential gene expression have been suggested, but some of these approaches are underpowered and result in high false positive rates because within-gene variance estimates are based on a small number of replicated arrays. Results: We propose to use local-pooled-error (LPE) estimates and robust statistical tests for evaluating significance of each gene's differential expression. Our LPE estimation is based on pooling errors within genes and between replicate arrays for genes in which expression values are similar. We have applied our LPE method to compare gene expression in naive and activated CD8(+) T-cells. Our results show that the LPE method effectively identifies significant differential-expression patterns with a small number of replicated arrays.
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