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Hierarchical Hidden Markov Model With Application To Joint Analysis Of Chip-Chip And Chip-Seq Data, Hyungwon Choi, Debashis Ghosh, Zhaohui S. Qin
Hierarchical Hidden Markov Model With Application To Joint Analysis Of Chip-Chip And Chip-Seq Data, Hyungwon Choi, Debashis Ghosh, Zhaohui S. Qin
Debashis Ghosh
Motivation: Identication of transcription factor binding sites (TFBS) is a fundamental problem in understanding the mechanism of gene regulation. The ChIP-chip technology has accelerated this eort by providing a simultaneous genome-wide map of TFBS in a high-throughput fashion. Recently, a sequencing-based ChIP-seq has appeared as a promising alternative that can identify targets with an improved sensitivity/specicity in high resolution. However, studies have suggested that distinct experimental platforms can be complementary in TFBS identication. The availability of data obtained from multiple platforms motivates a meta-analysis for improved identication of candidate motifs.
Results: In this work, we propose a hierarchical hidden Markov …