TY - JOUR T1 - BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes JF - bioRxiv DO - 10.1101/093393 SP - 093393 AU - Ines de Santiago AU - Wei Liu AU - Martin O’Reilly AU - Ke Yuan AU - Chandra Sekhar Reddy Chilamakuri AU - Bruce A.J. Ponder AU - Kerstin B. Meyer AU - Florian Markowetz Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/12/12/093393.abstract N2 - 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. ER -