Correcting nucleotide-specific biases in high-throughput sequencing data

BMC Bioinformatics

Methodology Article

Jeremy R. Wang¹  Terrence S. Furey²  Bryan Quach³ 

[1] Department of Genetics, University of North Carolina at Chapel Hill, CB 7032, 7314 Medical Biomolecular Research Building, 111 Mason Farm Road, 27599, Chapel Hill, NC, USA;Department of Genetics, University of North Carolina at Chapel Hill, CB 7032, 7314 Medical Biomolecular Research Building, 111 Mason Farm Road, 27599, Chapel Hill, NC, USA;Department of Biology, Carolina Center for Genome Sciences, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;

关键词: Epigenomics;    Bias correction;    DNase-seq;    ATAC-seq;    ChIP-seq;    FAIRE-seq;   

DOI  :  10.1186/s12859-017-1766-x

 received in 2017-02-09, accepted in 2017-07-19,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundHigh-throughput sequence (HTS) data exhibit position-specific nucleotide biases that obscure the intended signal and reduce the effectiveness of these data for downstream analyses. These biases are particularly evident in HTS assays for identifying regulatory regions in DNA (DNase-seq, ChIP-seq, FAIRE-seq, ATAC-seq). Biases may result from many experiment-specific factors, including selectivity of DNA restriction enzymes and fragmentation method, as well as sequencing technology-specific factors, such as choice of adapters/primers and sample amplification methods.ResultsWe present a novel method to detect and correct position-specific nucleotide biases in HTS short read data. Our method calculates read-specific weights based on aligned reads to correct the over- or underrepresentation of position-specific nucleotide subsequences, both within and adjacent to the aligned read, relative to a baseline calculated in assay-specific enriched regions. Using HTS data from a variety of ChIP-seq, DNase-seq, FAIRE-seq, and ATAC-seq experiments, we show that our weight-adjusted reads reduce the position-specific nucleotide imbalance across reads and improve the utility of these data for downstream analyses, including identification and characterization of open chromatin peaks and transcription-factor binding sites.ConclusionsA general-purpose method to characterize and correct position-specific nucleotide sequence biases fills the need to recognize and deal with, in a systematic manner, binding-site preference for the growing number of HTS-based epigenetic assays. As the breadth and impact of these biases are better understood, the availability of a standard toolkit to correct them will be important.

【 授权许可】

CC BY   
© The Author(s) 2017

【 图 表 】

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