ChIPmeta
Application data |
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Biological application domain(s) | Transcription Factor Binding Site identification, ChIP-Seq, ChIP-on-chip |
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Principal bioinformatics method(s) | Hidden Markov Model |
Maintained? | Maybe |
Summary: Combining data from ChIP-seq and ChIP-chip.
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In HHMM, inference results from individual HMMs in ChIP-seq and ChIP-chip experiments are summarized by a higher level HMM. Simulation studies show the advantage of HHMM when data from both technologies co-exist. Analysis of two well-studied transcription factors, NRSF and CTCF, also suggests that HHMM yields improved TFBS identification in comparison to analyses using individual data sources or a simple merger of the two.