@article {de Santiago093393, author = {Ines de Santiago and Wei Liu and Martin O{\textquoteright}Reilly and Ke Yuan and Chandra Sekhar Reddy Chilamakuri and Bruce A.J. Ponder and Kerstin B. Meyer and Florian Markowetz}, title = {BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes}, elocation-id = {093393}, year = {2016}, doi = {10.1101/093393}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Allele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods to detect allelic imbalance assume diploid genomes.This assumption severely limits their applicability to cancer samples with frequent DNA copy number changes.Here we present a Bayesian statistical approach called BaalChIP to correct for the effect of backgroundallele frequency on the observed ChIP-seq read counts. BaalChIP allows the joint analysis of multiple ChIP-seq samples across a single variant and outperforms competing approaches in simulations. Using 548 ENCODE ChIP-seq and 6 targeted FAIRE-seq samples we show that BaalChIP effectively corrects allele-specific analysis for copy number variation and increases the power to detect putative cis-acting regulatory variants in cancer genomes.}, URL = {https://www.biorxiv.org/content/early/2016/12/12/093393}, eprint = {https://www.biorxiv.org/content/early/2016/12/12/093393.full.pdf}, journal = {bioRxiv} }