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- Title
iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets.
- Authors
Yingying Wei; Xia Li; Qian-fei Wang; Hongkai Ji
- Abstract
Background: ChIP-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. Results: We 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. Conclusions: iASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB.
- Subjects
DNA-protein interactions; ALLELES; TRANSCRIPTION factors; HISTONE genetics; DATA integration; GENE mapping; GENETIC carriers
- Publication
BMC Genomics, 2012, Vol 13, Issue 1, p1
- ISSN
1471-2164
- Publication type
Article
- DOI
10.1186/1471-2164-13-681