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BioinformaticsBioinformatics
Peer-reviewed journal article

ERVcaller: Identify polymorphic endogenous retrovirus (ERV) and other transposable element (TE) insertions using whole-genome sequencing data

Xun CheniD, Dawei LiiD

Abstract

MotivationApproximately 8% of the human genome is derived from endogenous retroviruses (ERVs). In recent years, an increasing number of human diseases have been found to be associated with ERVs. However, it remains challenging to accurately detect the full spectrum of polymorphic (unfixed) ERVs using next-generation sequencing (NGS) data.\n\nResultsWe designed a new tool, ERVcaller, to detect and genotype transposable element (TE) insertions, including ERVs, in the human genome. We evaluated ERVcaller using both simulated and real benchmark whole-genome sequencing (WGS) datasets. By comparing with existing tools, ERVcaller consistently obtained both the highest sensitivity and precision for detecting simulated ERV and other TE insertions derived from real polymorphic TE sequences. For the WGS data from the 1000 Genomes Project, ERVcaller detected the largest number of TE insertions per sample based on consensus TE loci. By analyzing the experimentally verified TE insertions, ERVcaller had 94.0% TE detection sensitivity and 96.6% genotyping accuracy. PCR and Sanger sequencing in a small sample set verified 86.7% of examined insertion statuses and 100% of examined genotypes. In conclusion, ERVcaller is capable of detecting and genotyping TE insertions using WGS data with both high sensitivity and precision. This tool can be applied broadly to other species.\n\nAvailabilitywww.uvm.edu/genomics/software/ERVcaller.html\n\nContactdawei.li@uvm.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

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