Abstract
BackgroundHigh-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content.ResultsWe develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. Availability: The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at “http://aluru-sun.ece.iastate.edu/doku.php?id=redeem”.ConclusionsWe introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors for genomes with high repeat content.
Highlights
High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes
Short read technologies have been widely adopted for both genome sequencing and resequencing applications; development of high quality short read assemblers (e.g., [3,4,5,6,7]) and short read mapping tools that map reads to a reference genome [8,9] are important
We further develop an error correction method to transform erroneous bases in each read to the correct ones and compare the results with SHREC [12] and Reptile [13], two of the most recent error correction methods
Summary
High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. High throughput generation sequencing has revolutionized genomics, making it possible to sequence new genomes or resequence individual genomes at a manifold cheaper cost and in an order of magnitude less time than earlier Sanger sequencing. With this technology, ambitious genome sequencing projects target many organisms rather than a few, and large scale studies of high quality short read assemblers (e.g., [3,4,5,6,7]) and short read mapping tools that map reads to a reference genome [8,9] are important. Error removal or correction is necessary to keep the size of the graph manageable [7,10] and simplify non-repetitive read mapping [11]
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