Low-level variant calling for non-matched samples using a position-based and nucleotide-specific approach.

Low-level variant calling for non-matched samples using a position-based and nucleotide-specific approach.
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DOI:
10.1186/s12859-021-04090-y
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发表时间:
2021-04-08
期刊:
影响因子:
3
通讯作者:
Biesecker LG
Biesecker LG
中科院分区:
生物学4区
文献类型:
--
作者:
Dudley JN;Hong CS;Hawari MA;Shwetar J;Sapp JC;Lack J;Shiferaw H;NISC Comparative Sequencing Program;Johnston JJ;Biesecker LG

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The widespread use of next-generation sequencing has identified an important role for somatic mosaicism in many diseases. However, detecting low-level mosaic variants from next-generation sequencing data remains challenging. Here, we present a method for Position-Based Variant Identification (PBVI) that uses empirically-derived distributions of alternate nucleotides from a control dataset. We modeled this approach on 11 segmental overgrowth genes. We show that this method improves detection of single nucleotide mosaic variants of 0.01–0.05 variant allele fraction compared to other low-level variant callers. At depths of 600 × and 1200 ×, we observed > 85% and > 95% sensitivity, respectively. In a cohort of 26 individuals with somatic overgrowth disorders PBVI showed improved signal to noise, identifying pathogenic variants in 17 individuals. PBVI can facilitate identification of low-level mosaic variants thus increasing the utility of next-generation sequencing data for research and diagnostic purposes. The online version contains supplementary material available at 10.1186/s12859-021-04090-y.
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期刊: Genetics in medicine : official journal of the American College of Medical Genetics
影响因子: --
作者:
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发表时间: 2016-06
影响因子: 2
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发表时间: 2012-04
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Izawa K;Hijikata A;Tanaka N;Kawai T;Saito MK;Goldbach-Mansky R;Aksentijevich I;Yasumi T;Nakahata T;Heike T;Nishikomori R;Ohara O
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