title: Chipper: discovering transcription-factor targets from chromatin immunoprecipitation microarrays using variance stabilization.
abstract: Chromatin immunoprecipitation combined with microarray technology (Chip2) allows genome-wide determination of protein-DNA binding sites. The current standard method for analyzing Chip2 data requires additional control experiments that are subject to systematic error. We developed methods to assess significance using variance stabilization, learning error-model parameters without external control experiments. The method was validated experimentally, shows greater sensitivity than the current standard method, and incorporates false-discovery rate analysis. The corresponding software ('Chipper') is freely available. The method described here should help reveal an organism's transcription-regulatory 'wiring diagram'.
authors.affiliation: Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Longwood Avenue, Boston, MA 02115, USA. fgibbons@hms.harvard.edu
authors.forename: Francis D
authors.initials: FD
authors.lastname: Gibbons
authors.forename: Markus
authors.initials: M
authors.lastname: Proft
authors.forename: Kevin
authors.initials: K
authors.lastname: Struhl
authors.forename: Frederick P
authors.initials: FP
authors.lastname: Roth
mesh_terms: D000704:Analysis of Variance; D047369:Chromatin Immunoprecipitation; D019295:Computational Biology / Q000379:methods*; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D011401:Promoter Regions, Genetic; D012984:Software; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors