Teaser: Individualized benchmarking and optimization of read mapping results for NGS data.

Teaser: Individualized benchmarking and optimization of read mapping results for NGS data.

Abstract

Mapping reads to a genome remains challenging, especially for non-model organisms with lower quality assemblies, or for organisms with higher mutation rates. While most research has focused on speeding up the mapping process, little attention has been paid to optimize the choice of mapper and parameters for a user’s dataset. Here, we present Teaser, a software that assists in these choices through rapid automated benchmarking of different mappers and parameter settings for individualized data. Within minutes, Teaser completes a quantitative evaluation of an ensemble of mapping algorithms and parameters. We use Teaser to demonstrate how Bowtie2 can be optimized for different data.

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Authors
  • Smolka, Moritz
  • von Haeseler, Arndt
  • Sedlazeck, Fritz
  • Rescheneder, Philipp
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Shortfacts
Category
Journal Paper
Divisions
Bioinformatics and Computational Biology
Subjects
Informatik Sonstiges
Journal or Publication Title
Genome Biology: biology for the post-genomic era
ISSN
1474-760X
Publisher
BioMed Central Ltd
Volume
16
Date
October 2015
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