Laboratory of Animal Genetics, Department of Veterinary and Biosciences, Faculty of Veterinary Medicine, Ghent University, Heidestraat 19, 9820, Merelbeke, Belgium.
Small Animal Department, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820, Merelbeke, Belgium.
BMC Bioinformatics. 2023 Aug 1;24(1):305. doi: 10.1186/s12859-023-05426-6.
Since the introduction of next-generation sequencing (NGS) techniques, whole-exome sequencing (WES) and whole-genome sequencing (WGS) have not only revolutionized research, but also diagnostics. The gradual switch from single gene testing to WES and WGS required a different set of skills, given the amount and type of data generated, while the demand for standardization remained. However, most of the tools currently available are solely applicable for human analysis because they require access to specific databases and/or simply do not support other species. Additionally, a complicating factor in clinical genetics in animals is that genetic diversity is often dangerously low due to the breeding history. Combined, there is a clear need for an easy-to-use, flexible tool that allows standardized data processing and preferably, monitoring of genetic diversity as well. To fill these gaps, we developed the R-package variantscanR that allows an easy and straightforward identification and prioritization of known phenotype-associated variants identified in dogs and other domestic animals.
The R-package variantscanR enables the filtering of variant call format (VCF) files for the presence of known phenotype-associated variants and allows for the estimation of genetic diversity using multi-sample VCF files. Next to this, additional functions are available for the quality control and processing of user-defined input files to make the workflow as easy and straightforward as possible. This user-friendly approach enables the standardisation of complex data analysis in clinical settings.
We developed an R-package for the identification of known phenotype-associated variants and calculation of genetic diversity.
自下一代测序(NGS)技术问世以来,外显子组测序(WES)和全基因组测序(WGS)不仅彻底改变了研究,也改变了诊断。鉴于生成的数据量和类型,从单基因测试向 WES 和 WGS 的逐步转变需要一套不同的技能,而标准化的需求仍然存在。然而,目前大多数可用的工具仅适用于人类分析,因为它们需要访问特定的数据库,或者根本不支持其他物种。此外,动物临床遗传学中的一个复杂因素是,由于繁殖历史,遗传多样性通常非常低。总之,需要一种易于使用、灵活的工具,可以标准化数据处理,最好还可以监测遗传多样性。为了填补这些空白,我们开发了 R 包 variantscanR,它允许轻松、直接地识别和优先考虑在狗和其他家养动物中发现的与表型相关的已知变体。
R 包 variantscanR 允许根据已知表型相关变体的存在筛选变体调用格式(VCF)文件,并允许使用多样本 VCF 文件估计遗传多样性。除此之外,还提供了其他功能,用于质量控制和处理用户定义的输入文件,以使工作流程尽可能简单和直接。这种用户友好的方法使临床环境中的复杂数据分析标准化成为可能。
我们开发了一个用于识别已知表型相关变体和计算遗传多样性的 R 包。