BioData MiningBioinformaticsPeer-reviewed journal article
LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants
Abdulrahman I. AlasiriiD, Konrad J. KarczewskiiD, Brian S. ColeiD, Bao‐Li LozaiD, Jason H. MooreiD, Sander W. van der LaaniD, Folkert Wouter AsselbergsiD, Brendan J. KeatingiD, Jessica van SetteniD
Abstract
MotivationLoss-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. 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. ResultsWe have developed the Loss-of-Function ToolKit (LoFTK), which allows efficient and automated prediction of LoF variants from both genotyped 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. Availability and implementationLoFTK is an open source software and is freely available to non-commercial users at https://github.com/CirculatoryHealth/LoFTK Contactj.vansetten@umcutrecht.nl Supplementary informationSupplementary data are available at Bioinformatics online.
- organism: human
- assay: whole-exome sequencing
- research focus: variant calling
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 10
- FWCI
- 1.66
- Field percentile
- top 17%
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