Department of Evolutionary Genetics, Program in Evolutionary Biology, Uppsala University, Uppsala, Sweden.
Department of Organismal Biology, Program in Systematic Biology, Uppsala University, Uppsala, Sweden.
Bioinformatics. 2018 Nov 15;34(22):3929-3930. doi: 10.1093/bioinformatics/bty448.
Phylogenomic datasets invariably contain undetected stretches of non-homologous characters due to poor-quality sequences or erroneous gene models. The large-scale multi-gene nature of these datasets renders impractical or impossible detailed manual curation of sequences, but few tools exist that can automate this task. To address this issue, we developed a new method that takes as input a set of unaligned homologous sequences and uses an explicit probabilistic approach to identify and mask regions with non-homologous adjacent characters. These regions are defined as sharing no statistical support for homology with any other sequence in the set, which can result from e.g. sequencing errors or gene prediction errors creating frameshifts. Our methodology is implemented in the program PREQUAL, which is a fast and accurate tool for high-throughput filtering of sequences. The program is primarily aimed at amino acid sequences, although it can handle protein coding DNA sequences as well. It is fully customizable to allow fine-tuning of the filtering sensitivity.
The program PREQUAL is written in C/C++ and available through a GNU GPL v3.0 at https://github.com/simonwhelan/prequal.
Supplementary data are available at Bioinformatics online.
由于序列质量差或基因模型错误,系统发育基因组数据集不可避免地包含未检测到的非同源字符序列。这些数据集具有大规模的多基因性质,使得详细的手动序列编辑变得不切实际或不可能,但很少有工具可以自动完成此任务。为了解决这个问题,我们开发了一种新方法,该方法将一组未对齐的同源序列作为输入,并使用显式概率方法来识别和屏蔽具有非同源相邻字符的区域。这些区域被定义为与集合中的任何其他序列没有同源性的统计支持,这可能是由于测序错误或基因预测错误导致移码。我们的方法学在程序 PREQUAL 中实现,该程序是一种用于高通量过滤序列的快速而准确的工具。该程序主要针对氨基酸序列,但也可以处理蛋白质编码 DNA 序列。它可以完全定制,以允许微调过滤灵敏度。
程序 PREQUAL 是用 C/C++编写的,并通过 GNU GPL v3.0 在 https://github.com/simonwhelan/prequal 上提供。
补充数据可在 Bioinformatics 在线获得。