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Differential analysis of DNA microarray gene expression data
Author(s) -
Hatfield G. Wesley,
Hung Shepin,
Baldi Pierre
Publication year - 2003
Publication title -
molecular microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.857
H-Index - 247
eISSN - 1365-2958
pISSN - 0950-382X
DOI - 10.1046/j.1365-2958.2003.03298.x
Subject(s) - biology , dna microarray , microarray analysis techniques , gene , computational biology , gene expression , microarray databases , dna , gene expression profiling , genetics , microarray , differential (mechanical device) , engineering , aerospace engineering
Summary Here, we review briefly the sources of experimental and biological variance that affect the interpretation of high‐dimensional DNA microarray experiments. We discuss methods using a regularized t ‐test based on a Bayesian statistical framework that allow the identification of differentially regulated genes with a higher level of confidence than a simple t ‐test when only a few experimental replicates are available. We also describe a computational method for calculating the global false‐positive and false‐negative levels inherent in a DNA microarray data set. This method provides a probability of differential expression for each gene based on experiment‐wide false‐positive and ‐negative levels driven by experimental error and biological variance.