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Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data.
Genome Res. 2010 Nov 24;
Authors: Pique-Regi R, Degner JF, Pai AA, Gaffney DJ, Gilad Y, Pritchard JK
Accurate functional annotation of regulatory elements is essential for understanding global gene regulation. Here, we report a genome-wide map of 827,000 transcription factor binding sites in human lymphoblastoid cell lines, which is comprised of sites corresponding to 239 position weight matrices of known transcription factor binding motifs, and 49 novel sequence motifs. To generate this map, we developed a probabilistic framework that integrates cell- or tissue-specific experimental data such as histone modifications and DNaseI cleavage patterns with genomic information such as gene annotation and evolutionary conservation. Comparison to empirical ChIP-seq data suggests that our method is highly accurate yet has the advantage of targeting many factors in a single assay. We anticipate that this approach will be a valuable tool for genome-wide studies of gene regulation in a wide variety of cell-types or tissues under diverse conditions.
PMID: 21106904 [PubMed - as supplied by publisher]
More...
Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data.
Genome Res. 2010 Nov 24;
Authors: Pique-Regi R, Degner JF, Pai AA, Gaffney DJ, Gilad Y, Pritchard JK
Accurate functional annotation of regulatory elements is essential for understanding global gene regulation. Here, we report a genome-wide map of 827,000 transcription factor binding sites in human lymphoblastoid cell lines, which is comprised of sites corresponding to 239 position weight matrices of known transcription factor binding motifs, and 49 novel sequence motifs. To generate this map, we developed a probabilistic framework that integrates cell- or tissue-specific experimental data such as histone modifications and DNaseI cleavage patterns with genomic information such as gene annotation and evolutionary conservation. Comparison to empirical ChIP-seq data suggests that our method is highly accurate yet has the advantage of targeting many factors in a single assay. We anticipate that this approach will be a valuable tool for genome-wide studies of gene regulation in a wide variety of cell-types or tissues under diverse conditions.
PMID: 21106904 [PubMed - as supplied by publisher]
More...