Abstract
BackgroundChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles.ResultsWe develop a new method iASeq to address this issue by jointly analyzing multiple ChIP-seq datasets. iASeq uses a Bayesian hierarchical mixture model to learn correlation patterns of allele-specificity among multiple proteins. Using the discovered correlation patterns, the model allows one to borrow information across datasets to improve detection of allelic imbalance. Application of iASeq to 77 ChIP-seq samples from 40 ENCODE datasets and 1 genomic DNA sample in GM12878 cells reveals that allele-specificity of multiple proteins are highly correlated, and demonstrates the ability of iASeq to improve allelic inference compared to analyzing each individual dataset separately.ConclusionsiASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB.
Highlights
ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB)
The analysis demonstrates the ability of iASeq to automatically integrate information from multiple datasets to significantly improve the detection of allelic imbalance. iASeq is implemented as an R package which is freely available from Bioconductor [35]
While our results show that most analyzed transcription factor (TF)/histone modification (HM) tend to be skewed toward the same direction, these results do not imply that these proteins are perfectly correlated in terms of allele-specificity at each and every SNP
Summary
ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). Gene expression, DNA methylation, transcription factor (TF) binding or histone modification (HM) can be allele-specific. These phenomena, known as allele-specific expression (ASE), allele-specific DNA methylation (ASM) and allele-specific binding (ASB, including both allele-specific TF binding and allele-specific histone modifications), can contribute to phenotypic diversity and may play important roles in adaptive evolution [1,2,3]. Many allele-specific (AS) events have been found to correlate with variants in genomic sequences [4,5,6,7,8,9,10,11]. Characterizing allelespecificity can help with linking genotypes to
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