Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data.
We present a fast, versatile and adaptive-multiscale algorithm for analyzing a wide-variety of DNA microarray data. Its primary application is in normalization of array data as well as subsequent identification of 'enriched targets', e.g. differentially expressed genes in expression profiling arrays and enriched sites in ChIP-on-chip experimental data. We show how to accommodate the unique characteristics of ChIP-on-chip data, where the set of 'enriched targets' is large, asymmetric and whose proportion to the whole data varies locally.


BACKGROUND
Supplementary figures, related preprint, free software as well as our raw DNA microarray data with PCR validations are available at http://www.math.umn.edu/~lerman/supp/bioinfo06 as well as Bioinformatics online.
Lerman
Gilad
G
Department of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. S.E., Minneapolis, MN 55455, USA. lerman@umn.edu
McQuown
Joseph
J
Blais
Alexandre
A
Dynlacht
Brian D
BD
Chen
Guangliang
G
Mishra
Bud
B
D000465:Algorithms; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D002874:Chromosome Mapping / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020543:Proteome / Q000378:metabolism*
D020543:Proteome