PT  - JOURNAL ARTICLE
AU  - Moritz Smolka
AU  - Philipp Rescheneder
AU  - Michael C. Schatz
AU  - Arndt von Haeseler
AU  - Fritz J. Sedlazeck
TI  - Teaser: Individualized benchmarking and optimization of read mapping results for NGS data
AID  - 10.1101/025858
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 025858
4099  - http://biorxiv.org/content/early/2015/09/01/025858.short
4100  - http://biorxiv.org/content/early/2015/09/01/025858.full
AB  - Mapping reads to a genome remains challenging, especially for non-model organisms with poorer quality assemblies, or for organisms with higher rates of mutations. 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, which 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. Using Teaser, we demonstrate how Bowtie2 can be optimized for different data.