Schilbert Hanna Marie, Rempel Andreas, Pucker Boas
Genetics and Genomics of Plants, CeBiTec and Faculty of Biology, Bielefeld University, 33615 Bielefeld, Germany.
Graduate School DILS, Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany.
Plants (Basel). 2020 Apr 2;9(4):439. doi: 10.3390/plants9040439.
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 . 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.
在过去几年中，高通量测序技术迅速发展，已成为植物科学中的一项重要工具。然而，基因组数据分析仍然具有挑战性，并且主要依赖于自动流程的性能。常用的流程包括将序列读数与参考序列进行比对以及识别序列变异。由于为此目的对生物信息学工具进行的大多数基准测试研究都是在人类数据集上进行的，因此植物科学领域缺乏基准测试研究。在本研究中，我们在模式生物的六个真实植物数据集上评估了50种不同的变异检测流程的性能，包括五种读数比对器和十种变异检测工具。基于包括灵敏度和特异性在内的各种参数对变异集进行了评估。我们发现所有研究的工具都适用于植物研究中的NGS数据分析。在查看不同的性能指标时，BWA-MEM和Novoalign是最佳的比对器，而GATK在变异检测步骤中返回了最佳结果。
