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Oxford University Press (OUP), Bioinformatics, 16(25), p. 2118-2125

DOI: 10.1093/bioinformatics/btp276

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Utilizing gene pair orientations for HMM-based analysis of promoter array ChIP-chip data

Journal article published in 2009 by Michael Seifert, Jens Keilwagen ORCID, Marc Strickert, Ivo Grosse
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Motivation: Array-based analysis of chromatin immunoprecipitation (ChIP-chip) data is a powerful technique for identifying DNA target regions of individual transcription factors. The identification of these target regions from comprehensive promoter array ChIP-chip data is challenging. Here, three approaches for the identification of transcription factor target genes from promoter array ChIP-chip data are presented. We compare (i) a standard log-fold-change analysis (LFC); (ii) a basic method based on a Hidden Markov Model (HMM); and (iii) a new extension of the HMM approach to an HMM with scaled transition matrices (SHMM) that incorporates information about the relative orientation of adjacent gene pairs on DNA.