Sam2bam: High-Performance Framework for NGS Data Preprocessing Tools

Takeshi Ogasawara; Yinhe Cheng; Tzy-Hwa Kathy Tzeng

doi:10.1371/journal.pone.0167100

Sam2bam: High-Performance Framework for NGS Data Preprocessing Tools

PLoS One. 2016 Nov 18;11(11):e0167100. doi: 10.1371/journal.pone.0167100. eCollection 2016.

Authors

Takeshi Ogasawara¹, Yinhe Cheng², Tzy-Hwa Kathy Tzeng³

Affiliations

¹ IBM Research-Tokyo, Tokyo, Japan.
² IBM Systems, Austin, TX, United States of America.
³ IBM Systems, Poughkeepsie, NY, United States of America.

Abstract

This paper introduces a high-throughput software tool framework called sam2bam that enables users to significantly speed up pre-processing for next-generation sequencing data. The sam2bam is especially efficient on single-node multi-core large-memory systems. It can reduce the runtime of data pre-processing in marking duplicate reads on a single node system by 156-186x compared with de facto standard tools. The sam2bam consists of parallel software components that can fully utilize multiple processors, available memory, high-bandwidth storage, and hardware compression accelerators, if available. The sam2bam provides file format conversion between well-known genome file formats, from SAM to BAM, as a basic feature. Additional features such as analyzing, filtering, and converting input data are provided by using plug-in tools, e.g., duplicate marking, which can be attached to sam2bam at runtime. We demonstrated that sam2bam could significantly reduce the runtime of next generation sequencing (NGS) data pre-processing from about two hours to about one minute for a whole-exome data set on a 16-core single-node system using up to 130 GB of memory. The sam2bam could reduce the runtime of NGS data pre-processing from about 20 hours to about nine minutes for a whole-genome sequencing data set on the same system using up to 711 GB of memory.

MeSH terms

Computational Biology* / methods
Exome
Genome
Genomics / methods
High-Throughput Nucleotide Sequencing*
Reproducibility of Results
Sequence Analysis, DNA / methods*
Software*

Grants and funding

The funder, IBM, provided support in the form of salaries for authors TO, YC and TKT, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.