Genome ResearchBioinformaticsPeer-reviewed journal article
Targeted Genotyping of Variable Number Tandem Repeats with adVNTR
Mehrdad BakhtiariiD, Sharona Shleizer-BurkoiD, Melissa GymrekiD, Vikas BansaliD, Vineet BafnaiD
Abstract
Whole Genome Sequencing is increasingly used to identify Mendelian variants in clinical pipelines. These pipelines focus on single nucleotide variants (SNVs) and also structural variants, while ignoring more complex repeat sequence variants. We consider the problem of genotyping Variable Number Tandem Repeats (VNTRs), composed of inexact tandem duplications of short (6-100bp) repeating units. VNTRs span 3% of the human genome, are frequently present in coding regions, and have been implicated in multiple Mendelian disorders. While existing tools recognize VNTR carrying sequence, genotyping VNTRs (determining repeat unit count and sequence variation) from whole genome sequenced reads remains challenging. We describe a method, adVNTR, that uses Hidden Markov Models to model each VNTR, count repeat units, and detect sequence variation. adVNTR models can be developed for short-read (Illumina) and single molecule (PacBio) whole genome and exome sequencing, and show good results on multiple simulated and real data sets. adVNTR is available at https://github.com/mehrdadbakhtiari/adVNTR
- organism: human
- assay: whole-genome sequencing
- assay: whole-exome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 86
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