RT Journal Article
SR Electronic
T1 BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 093393
DO 10.1101/093393
A1 Ines de Santiago
A1 Wei Liu
A1 Martin O’Reilly
A1 Ke Yuan
A1 Chandra Sekhar Reddy Chilamakuri
A1 Bruce A.J. Ponder
A1 Kerstin B. Meyer
A1 Florian Markowetz
YR 2016
UL http://biorxiv.org/content/early/2016/12/12/093393.abstract
AB 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.