期刊
BMC BIOINFORMATICS
卷 22, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s12859-021-04090-y
关键词
Mosaic variants; Prediction of mosaic variants; Somatic overgrowth disorder
类别
资金
- NIH [Z01 HG200328 14, Z01 HG200359 11]
PBVI is a method for Position-Based Variant Identification that improves the detection of low-level mosaic variants by using empirically-derived distributions of alternate nucleotides from a control dataset. Modeled on 11 segmental overgrowth genes, this method shows superior detection of single nucleotide mosaic variants of 0.01-0.05 variant allele fraction. Sensitivity of over 85% and 95% was observed at depths of 600 x and 1200 x, respectively, demonstrating its utility in identifying pathogenic variants in individuals with somatic overgrowth disorders.
Background 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. Results 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 x and 1200 x, 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. Conclusion PBVI can facilitate identification of low-level mosaic variants thus increasing the utility of next-generation sequencing data for research and diagnostic purposes.
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