Alasiri Abdulrahman, Karczewski Konrad J, Cole Brian, Loza Bao-Li, Moore Jason H, van der Laan Sander W, Asselbergs Folkert W, Keating Brendan J, van Setten Jessica
Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, Netherlands.
Medical Genomics Research Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.
BioData Min. 2023 Feb 2;16(1):3. doi: 10.1186/s13040-023-00321-5.
Loss-of-Function (LoF) variants in human genes are important due to their impact on clinical phenotypes and frequent occurrence in the genomes of healthy individuals. The association of LoF variants with complex diseases and traits may lead to the discovery and validation of novel therapeutic targets. Current approaches predict high-confidence LoF variants without identifying the specific genes or the number of copies they affect. Moreover, there is a lack of methods for detecting knockout genes caused by compound heterozygous (CH) LoF variants.
We have developed the Loss-of-Function ToolKit (LoFTK), which allows efficient and automated prediction of LoF variants from genotyped, imputed and sequenced genomes. LoFTK enables the identification of genes that are inactive in one or two copies and provides summary statistics for downstream analyses. LoFTK can identify CH LoF variants, which result in LoF genes with two copies lost. Using data from parents and offspring we show that 96% of CH LoF genes predicted by LoFTK in the offspring have the respective alleles donated by each parent.
LoFTK is a command-line based tool that provides a reliable computational workflow for predicting LoF variants from genotyped and sequenced genomes, identifying genes that are inactive in 1 or 2 copies. LoFTK is an open software and is freely available to non-commercial users at https://github.com/CirculatoryHealth/LoFTK .
人类基因中的功能丧失（LoF）变异很重要，因为它们会影响临床表型，且在健康个体的基因组中频繁出现。LoF变异与复杂疾病和性状的关联可能会促成新治疗靶点的发现与验证。当前方法可预测高可信度的LoF变异，但无法识别具体基因或其所影响的拷贝数。此外，缺乏检测由复合杂合（CH）LoF变异导致的敲除基因的方法。
我们开发了功能丧失工具包（LoFTK），它能从基因分型、推断和测序的基因组中高效且自动地预测LoF变异。LoFTK能够识别单拷贝或双拷贝失活的基因，并为下游分析提供汇总统计信息。LoFTK可以识别CH LoF变异，即导致两个拷贝均失活的基因。利用来自父母和后代的数据，我们发现LoFTK在后代中预测的CH LoF基因，96%都有来自每个亲本的相应等位基因。
LoFTK是一个基于命令行的工具，它为从基因分型和测序基因组中预测LoF变异、识别单拷贝或双拷贝失活的基因提供了可靠的计算工作流程。LoFTK是一款开源软件，非商业用户可在https://github.com/CirculatoryHealth/LoFTK上免费获取。
