LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes

Publication date

2023-12

Authors

Alasiri, A I
Karczewski, Konrad J.
Cole, Brian
Loza, Bao Li
Moore, Jason H.
van der Laan, Sander W.ORCID 0000-0001-6888-1404
Asselbergs, Folkert WORCID 0000-0002-1692-8669ISNI 0000000391548591
Keating, Brendan J.
Van Setten, JessicaORCID 0000-0002-4934-7510ISNI 0000000390875734

Editors

Advisors

Supervisors

Document Type

Article

Collections

Open Access logo

License

cc_by

Abstract

Background: 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. Results: 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. Conclusions: 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.

Keywords

Compound heterozygotes, Human genetic, Knockout genes, Loss-of-Function variants, Biochemistry, Molecular Biology, Genetics, Computer Science Applications, Computational Theory and Mathematics, Computational Mathematics

Citation

Alasiri, A, Karczewski, K J, Cole, B, Loza, B L, Moore, J H, van der Laan, S W, Asselbergs, F W, Keating, B J & van Setten, J 2023, 'LoFTK : a framework for fully automated calculation of predicted Loss-of-Function variants and genes', BioData Mining, vol. 16, no. 1, 3. https://doi.org/10.1186/s13040-023-00321-5