Teaser: Individualized benchmarking and optimization of read mapping results for NGS data
Moritz SmolkaiD, Philipp Rescheneder, Michael C Schatz, Arndt von HaeseleriD, Fritz J Sedlazeck
Abstract
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 users 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.
02 /Specification & Classification
Click any tag to browse matching papers- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Whisper: Read sorting allows robust mapping of sequencing data
Sebastian Deorowicz, Agnieszka Debudaj-Grabysz, … Szymon Grabowski·BioinformaticsPeer-reviewed·Nov 6, 2018
- URMAP, an ultra fast read mapper
R. C. Edgar·PeerJPeer-reviewed·Jun 24, 2020
- benchNGS : An approach to benchmark short reads alignment tools
Farzana Rahman, Mehedi Hassan, … Tatiana Tatarinova·bioRxiv·Apr 18, 2015
- Context-Aware Seeds for Read Mapping
Hongyi Xin, Mingfu Shao, Carl Kingsford·Algorithms for Molecular BiologyPeer-reviewed·May 23, 2020
- BisPin and BFAST-Gap: Mapping Bisulfite-Treated Reads
Jacob Porter, Liqing Zhang·bioRxiv·Jun 16, 2018
- MMR: A Tool for Read Multi-Mapper Resolution
Andre Kahles, Jonas Behr, Gunnar Rätsch·BioinformaticsPeer-reviewed·Oct 30, 2015