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This paper introduces a high-throughput software tool framework called {\itsam2bam} that enables users to significantly speedup pre-processing fornext-generation sequencing data. The sam2bam is especially efficient onsingle-node multi-core large-memory systems. It can reduce the runtime of datapre-processing in marking duplicate reads on a single node system by 156-186xcompared with de facto standard tools. The sam2bam consists of parallelsoftware components that can fully utilize the multiple processors, availablememory, high-bandwidth of storage, and hardware compression accelerators ifavailable.  The sam2bam provides file format conversion between well-known genome fileformats, from SAM to BAM, as a basic feature. Additional features such asanalyzing, filtering, and converting the input data are provided by {\itplug-in} tools, e.g., duplicate marking, which can be attached to sam2bam atruntime.  We demonstrated that sam2bam could significantly reduce the runtime of NGSdata pre-processing from about two hours to about one minute for a whole-exomedata set on a 16-core single-node system using up to 130 GB of memory. Thesam2bam could reduce the runtime for whole-genome sequencing data from about 20hours to about nine minutes on the same system using up to 711 GB of memory.

Sam2bam: High-Performance Framework for NGS Data Preprocessing Tools