Fast personalized benchmarks and optimization for NGS read mapping.

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...a suitable mapper for your next-gen sequencing data in minutes


...the right mapping quality thresholds for filtering


...mapper parameters for accuracy or throughput


...simulation and real data results

Teaser analyzes the performance of read mappers based on a data set provided by you. After you enter key characteristics such as read length and reference genome, Teaser will simulate read data including the gold standard alignment. After the simulation, Teaser automatically runs and evaluates each mapper for the selected parameters and summarizes the results in a report. Teaser also supports benchmarking mappers on real data or custom simulations, as well as testing new mappers and custom parameter sets. You can start using Teaser right now using this web application, or download and install it to unlock all advanced features.

If you use Teaser to optimize read mapping in your study, please cite: Smolka M, Rescheneder P, Schatz MC, von Haeseler A and Sedlazeck FJ. Teaser: Individualized benchmarking and optimization of read mapping results for NGS data. Genome Biology 2015, 16:235 (22 October 2015). DOI: 10.1186/s13059-015-0803-1
Recent Publications that cite Teaser
  • Therkildsen, Nina Overgaard, and Stephen R. Palumbi. "Practical lowcoverage genomewide sequencing of hundreds of individually barcoded samples for population and evolutionary genomics in nonmodel species." Molecular ecology resources 17.2 (2017): 194-208.

  • Dennenmoser, Stefan, et al. "Adaptive genomic divergence under high gene flow between freshwater and brackishwater ecotypes of prickly sculpin (Cottus asper) revealed by PoolSeq." Molecular ecology 26.1 (2017): 25-42.

  • Vurture, Gregory W., et al. "GenomeScope: Fast reference-free genome profiling from short reads." Bioinformatics (2017): btx153.

  • Guzman, Carlos, and Ivan D'Orso. "CIPHER: a flexible and extensive workflow platform for integrative next-generation sequencing data analysis and genomic regulatory element prediction." BMC bioinformatics 18.1 (2017): 363.

  • Pfeifer, S. P. "From next-generation resequencing reads to a high-quality variant data set." Heredity (2016).

  • Brinda, Karel. Novel computational techniques for mapping and classifying Next-Generation Sequencing data. Diss. Universite Paris-Est Marne-la-Valle, 2016.
Update News

New Teaser Version 01/09/2016

Teaser 1.2 is now available and includes various features such as updated visualization, configuration for the segemehl, CUSHAW3, Stampy and Bowtie mappers and improvements in read simulation.

Teaser Published10/22/2015

We are happy to announce the publication of Teaser in Genome Biology! Link to Article

Public Version Available 08/12/2015

Version 1.0f of the Teaser framework is now available for public use on the CIBIV servers.
Recent Benchmarks
Teaser Accession Organism Date Platform Library Read Length
3f152d22cbb94ef1486badb39c2ab129H_sapiens2020-10-26 20:58:38illuminapaired-end150
e31278c88d8355134480413598eea2dbE_coli2020-10-20 08:53:43illuminasingle-end60
70af518a8b48e0d2bb8543d854af195cH_sapiens2020-09-27 16:00:49illuminasingle-end100
87dcb82101244e42987c8f03783d1389Saccharomyces_cerevisiae2020-09-23 16:02:16illuminapaired-end150
7a8a75a1c637f0ebbc89ec47aabdc704Saccharomyces_cerevisiae2020-09-23 15:39:43illuminapaired-end150
e9b1ae4a334ade1b06ceaf9cdccbab2aSaccharomyces_cerevisiae2020-09-23 15:39:21illuminapaired-end150
83b14ddb61122a5642d433d5b5e02dc1Saccharomyces_cerevisiae2020-09-23 15:38:39illuminapaired-end150
d031593a6d512b02a40b3e212d492e26Saccharomyces_cerevisiae2020-09-23 15:38:14illuminapaired-end150
49efdcc8427d5b82e5ad0decc124406eSaccharomyces_cerevisiae2020-09-23 15:34:23illuminapaired-end150
e925f83e13dde3c4e512eb71ba79d3b4Saccharomyces_cerevisiae2020-09-23 15:32:18illuminapaired-end150

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