Improving read mapping using additional prefix grams

Abstract

BackgroundNext-generation sequencing (NGS) enables rapid production of billions of bases at a relatively low cost. Mapping reads from next-generation sequencers to a given reference genome is an important first step in many sequencing applications. Popular read mappers, such as Bowtie and BWA, are optimized to return top one or a few candidate locations of each read. However, identifying all mapping locations of each read, instead of just one or a few, is also important in some sequencing applications such as ChIP-seq for discovering binding sites in repeat regions, and RNA-seq for transcript abundance estimation.ResultsHere we present Hobbes2, a software package designed for fast and accurate alignment of NGS reads and specialized in identifying all mapping locations of each read. Hobbes2 efficiently identifies all mapping locations of reads using a novel technique that utilizes additional prefix q-grams to improve filtering. We extensively compare Hobbes2 with state-of-the-art read mappers, and show that Hobbes2 can be an order of magnitude faster than other read mappers while consuming less memory space and achieving similar accuracy.ConclusionsWe propose Hobbes2 to improve the accuracy of read mapping, specialized in identifying all mapping locations of each read. Hobbes2 is implemented in C++, and the source code is freely available for download at http://hobbes.ics.uci.edu.

AMAS: Optimizing the Partition and Filtration of Adaptive Seeds to Speed up Read Mapping

“…total e+2=7 seeds, achieved the best overall mapping time (Supplementary Table S1). This is similar to the observation in Hobbes 2 [21], GSNAP [25].…”

“…In this section, we compare the performance of AMAS and the latest state-of-the-art all-mappers GEM [18], Masai [19], Hobbes 2 [21], mrFAST (with FastHASH) [16], and mrsFAST-ultra [15]. We also included two popular best-mappers Bowtie 2 and BWA in the comparison.…”

“…Following previous studies of Masai and Hobbes 2 [19,21], we used the Rabema benchmark [30] to measure the sensitivity of the mappers. First, RazerS 3 [17] was run in its full-sensitive mode to build the gold-standard set of all possible mapping locations with up to 5 errors.…”

“…This all-mapping task is highly essential in several applications such as prediction of genomic variants or protein binding motifs located in repeat regions, isoform expression quantification, metagenomics analysis [9][10][11][12]. Some prominent allmappers include SOAP 2 [13], SHRiMP 2 [14], mrsFAST [10,15], mrFAST [9,16], RazerS 3 [17], GEM [18], Masai [19], Hobbes 1, 2 [20,21].…”

“…Instead of partitioning the read into contiguous seeds, Hobbes considers all possible partitions and applies a dynamic programming to select the one that minimizes the sum of frequencies of the seeds. In the latest version, Hobbes 2 [21], the authors further suggested to use extra seeds to improve filtering specificity: instead of e+1, e+2 (or more) non-overlapping seeds can be employed. Then, by the pigeonhole principle, at least two of those seeds must have exact matches in the reference sequence and hence only those locations reported by at least two seeds will be selected as candidates for the extension step.…”