A prerequisite for utilizing the public ChIP data is the ability to freely query, retrieve, normalize and compare binding intensities from arbitrary samples and genomic regions. Currently, this is a daunting task for most researchers working on human and mouse. Existing raw data repositories such as The NCBI Gene Expression Omnibus (GEO) [1] and Sequence Read Archive (SRA) [2] do not provide tools for interactively exploring the ChIP data. The UCSC genome browser [3] provides functionalities for visualizing the data, but its ChIP data collection is limited. Although the browser is good at exploring one genomic region at a time, it is incapable of conveniently retrieving, normalizing and comparing data from many genomic regions. The recently developed ChIP-X database [4] has collected TF target gene lists from published ChIP studies, however it does not provide tools for retrieving and comparing binding intensities across samples. hmChIP is developed in this context to meet the pressing need for exploring protein-DNA binding intensities in publicly available ChIP data.


[1]Barrett, T., Troup, D.B., Wilhite, S.E., et al. (2007) NCBI GEO: Mining tens of millions
of expression profiles -- database and tools update. Nucleic Acids Res., 35, D760-765.

[2]Wheeler, D.L., Barrett, T., Benson, D.A., et al. (2008) Database resources of the
National Center for Biotechnology Information. Nucleic Acids Res. 36, D13-21.

[3]Kent, W.J., Sugnet, C.W., Furey, T.S., et al. (2002) The human genome browser at
UCSC. Genome Res. 12, 996-1006.

[4]Lachmann, A., Xu, H., Krishnan, J., et al. (2010). ChEA: transcription factor regulation
inferred from integrating genome-wide ChIP-X experiments. Bioinformatics, 26, 2438-44.

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    Li Chen

    Dept. of Biostatistics

    Johns Hopkins Univ