Next Article in Journal
Water Influx through the Wetted Surface of a Sweet Cherry Fruit: Evidence for an Associated Solute Efflux
Previous Article in Journal
In Vitro Antifungal Activity of Peltophorum dubium (Spreng.) Taub. extracts against Aspergillus flavus
Article

Comparison of Read Mapping and Variant Calling Tools for the Analysis of Plant NGS Data

1
Genetics and Genomics of Plants, CeBiTec and Faculty of Biology, Bielefeld University, 33615 Bielefeld, Germany
2
Graduate School DILS, Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany
3
Molecular Genetics and Physiology of Plants, Faculty of Biology and Biotechnology, Ruhr-University Bochum, 44801 Bochum, Germany
*
Author to whom correspondence should be addressed.
Plants 2020, 9(4), 439; https://doi.org/10.3390/plants9040439
Received: 15 March 2020 / Revised: 28 March 2020 / Accepted: 30 March 2020 / Published: 2 April 2020
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
High-throughput sequencing technologies have rapidly developed during the past years and have become an essential tool in plant sciences. However, the analysis of genomic data remains challenging and relies mostly on the performance of automatic pipelines. Frequently applied pipelines involve the alignment of sequence reads against a reference sequence and the identification of sequence variants. Since most benchmarking studies of bioinformatics tools for this purpose have been conducted on human datasets, there is a lack of benchmarking studies in plant sciences. In this study, we evaluated the performance of 50 different variant calling pipelines, including five read mappers and ten variant callers, on six real plant datasets of the model organism Arabidopsis thaliana. Sets of variants were evaluated based on various parameters including sensitivity and specificity. We found that all investigated tools are suitable for analysis of NGS data in plant research. When looking at different performance metrics, BWA-MEM and Novoalign were the best mappers and GATK returned the best results in the variant calling step. View Full-Text
Keywords: Single Nucleotide Variants (SNVs); Single Nucleotide Polymorphisms (SNPs); Insertions/Deletions (InDels); population genomics; re-sequencing; mapper; benchmarking; Next Generation Sequencing (NGS); bioinformatics; plant genomics Single Nucleotide Variants (SNVs); Single Nucleotide Polymorphisms (SNPs); Insertions/Deletions (InDels); population genomics; re-sequencing; mapper; benchmarking; Next Generation Sequencing (NGS); bioinformatics; plant genomics
Show Figures

Figure 1

MDPI and ACS Style

Schilbert, H.M.; Rempel, A.; Pucker, B. Comparison of Read Mapping and Variant Calling Tools for the Analysis of Plant NGS Data. Plants 2020, 9, 439. https://doi.org/10.3390/plants9040439

AMA Style

Schilbert HM, Rempel A, Pucker B. Comparison of Read Mapping and Variant Calling Tools for the Analysis of Plant NGS Data. Plants. 2020; 9(4):439. https://doi.org/10.3390/plants9040439

Chicago/Turabian Style

Schilbert, Hanna M., Andreas Rempel, and Boas Pucker. 2020. "Comparison of Read Mapping and Variant Calling Tools for the Analysis of Plant NGS Data" Plants 9, no. 4: 439. https://doi.org/10.3390/plants9040439

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop