BBMerge - Accurate paired shotgun read merging via overlap

Abstract

Merging paired-end shotgun reads generated on high-throughput sequencing platforms can substantially improve various subsequent bioinformatics processes, including genome assembly, binning, mapping, annotation, and clustering for taxonomic analysis. With the inexorable growth of sequence data volume and CPU core counts, the speed and scalability of read-processing tools becomes ever-more important. The accuracy of shotgun read merging is crucial as well, as errors introduced by incorrect merging percolate through to reduce the quality of downstream analysis. Thus, we designed a new tool to maximize accuracy and minimize processing time, allowing the use of read merging on larger datasets, and in analyses highly sensitive to errors. We present BBMerge, a new merging tool for paired-end shotgun sequence data. We benchmark BBMerge by comparison with eight other widely used merging tools, assessing speed, accuracy and scalability. Evaluations of both synthetic and real-world datasets demonstrate that BBMerge produces merged shotgun reads with greater accuracy and at higher speed than any existing merging tool examined. BBMerge also provides the ability to merge non-overlapping shotgun read pairs by using k-mer frequency information to assemble the unsequenced gap between reads, achieving a significantly higher merge rate while maintaining or increasing accuracy.

Fig 1

Merging scenarios in BBMerge modes: default (A-B), REM (C-F), and RSEM (G-I). The left column (Fig 1A,C,D,F) displays scenarios resulting in successfully merged reads, while the right column (Fig 1B,E,G,H) displays scenarios resulting in discarded unmerged pairs.

Fig 2. Relationship between % merged reads and genome coverage.

Fig 3

Comparison of merging accuracy by program using synthetic (A) and shotgun metagenome sequences (B). Correctly merged reads are defined as % of total input pairs. Program performance at default sensitivity is indicated by a triangle.

Fig 4. Speed comparison by program of shotgun metagenome sequences.

Fig 5. Scalability of each program, determined by measuring speed using various numbers of threads.

Fig 6. NA50 length and misassembly rates for a SPAdes assembly of each program’s output at default settings.