research data . Dataset . 2016

Sam2bam: High-Performance Framework for NGS Data Preprocessing Tools

Ogasawara, Takeshi; Cheng, Yinhe; Tzeng, Tzy-Hwa Kathy;
  • Published: 01 Jan 2016
  • Publisher: Figshare
Abstract
<div><p>This paper introduces a high-throughput software tool framework called <i>sam2bam</i> 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 ...
Subjects
free text keywords: Genetics, Molecular Biology, Space Science, 69999 Biological Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified, next-generation sequencing data, sam 2bam, single-node multi-core large-memory systems, NGS data pre-processing, BAM, SAM, whole-genome sequencing data, hardware compression accelerators, Sam 2bam High-Performance Framework, runtime, high-throughput software tool framework, data pre-processing, 16- core single-node system, NGS Data Preprocessing Tools, GB
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Dataset . 2016
Provider: figshare
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