Abstract
With the rapid and steady increase of next generation sequencing data output, the mapping of short reads has become a major data analysis bottleneck. On a single computer, it can take several days to map the vast quantity of reads produced from a single Illumina HiSeq lane. In an attempt to ameliorate this bottleneck we present a new tool, DistMap - a modular, scalable and integrated workflow to map reads in the Hadoop distributed computing framework. DistMap is easy to use, currently supports nine different short read mapping tools and can be run on all Unix-based operating systems. It accepts reads in FASTQ format as input and provides mapped reads in a SAM/BAM format. DistMap supports both paired-end and single-end reads thereby allowing the mapping of read data produced by different sequencing platforms. DistMap is available from http://code.google.com/p/distmap/
Highlights
Generation Sequencing (NGS) technologies have revolutionized biological research by producing an unprecedented amount of data in a cost effective manner
We present a new tool, DistMap, a modular, scalable and user-friendly workflow, which facilitates the mapping of short reads on a Hadoop cluster [14]
DistMap provides an integrated workflow for short read mapping against a user-specified reference genome
Summary
Generation Sequencing (NGS) technologies have revolutionized biological research by producing an unprecedented amount of data in a cost effective manner. The first step in most NGS workflows is the mapping of short sequence reads to a reference genome. Galaxy [9] is another powerful workflow system but supports only BWA and bowtie mapping and imposes version restrictions for both the mapper and the reference sequence.
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