Correcting nucleotide-specific biases in high-throughput sequencing data

Jeremy R. Wang, Bryan Quach, Terrence S. Furey
2017 BMC Bioinformatics  
High-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
more » ... , such as choice of adapters/primers and sample amplification methods. Results: We 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. Conclusions: A 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. Background High-throughput short-read sequencing (HTS) has enabled the genome-wide identification of functional regulatory regions including transcription factor binding sites and epigenomic features such as histone tail modifications and regions of open chromatin. HTS-based assays such as ChIP-seq, DNase-seq, FAIRE-seq, and ATAC-seq generate millions of reads per experiment that then are used to identify regions of interest. However, a combination of biases in these HTS protocols often results in a deviation from the background frequency of nucleotides present at each position in HTS reads, which
doi:10.1186/s12859-017-1766-x pmid:28764645 pmcid:PMC5540620 fatcat:mgz6nzun5nhjnf7au27migcede