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CISMAPPER: predicting regulatory interactions from transcription factor ChIP-seq data
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Identifying the genomic regions and regulatory factors that control the transcription of genes is an important, unsolved problem. The current method of choice predicts transcription factor (TF) binding sites using chromatin immunoprecipitation followed by sequencing (ChIP- seq), and then links the binding sites to putative target genes solely on the basis of the genomic distance between them. Evidence from chromatin conformation capture experiments shows that this approach is inadequate due to long-distance regulation via chromatin looping. We present CISMAPPER, which predicts the regulatory targets of a TF using the correlation between a histone mark at the TF's bound sites and the expression of each gene across a panel of tissues. Using both chromatin conformation capture and differential expression data, we show that CISMAPPER is more accurate at predicting the target genes of a TF than the distance-based approaches currently used, and is particularly advantageous for predicting the long-range regulatory interactions typical of tissue-specific gene expression. CISMAPPER also predicts which TF binding sites regulate a given gene more accurately than using genomic distance. Unlike distance-based methods, CISMAPPER can predict which transcription start site of a gene is regulated by a particular binding site of the TF.