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

Bibliographic Details
Title: LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes
Authors: Abdulrahman Alasiri, Konrad J. Karczewski, Brian Cole, Bao-Li Loza, Jason H. Moore, Sander W. van der Laan, Folkert W. Asselbergs, Brendan J. Keating, Jessica van Setten
Source: BioData Mining, Vol 16, Iss 1, Pp 1-10 (2023)
Publisher Information: BMC, 2023.
Publication Year: 2023
Collection: LCC:Computer applications to medicine. Medical informatics
LCC:Analysis
Subject Terms: Loss-of-Function variants, Knockout genes, Compound heterozygotes, Human genetic, Computer applications to medicine. Medical informatics, R858-859.7, Analysis, QA299.6-433
More Details: 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 .
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1756-0381
Relation: https://doaj.org/toc/1756-0381
DOI: 10.1186/s13040-023-00321-5
Access URL: https://doaj.org/article/f8e71408467d4ef6916d54391004dd44
Accession Number: edsdoj.f8e71408467d4ef6916d54391004dd44
Database: Directory of Open Access Journals
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More Details
ISSN:17560381
DOI:10.1186/s13040-023-00321-5
Published in:BioData Mining
Language:English