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Platform comparison of detecting copy number variants with microarrays and whole-exome sequencing.

ABSTRACT: Copy number variation (CNV) is a common source of genetic variation that has been implicated in many genomic disorders, Mendelian diseases, and common/complex traits. Genomic microarrays are often employed for CNV detection. More recently, whole-exome sequencing (WES) has enabled detection of clinically relevant point mutations and small insertion-deletion exome wide. We evaluated (de Ligt et al. 2013) [1] the utility of short-read WES (SOLiD 5500xl) to detect clinically relevant CNVs in DNA from 10 patients with intellectual disability and compared these results to data from three independent high-resolution microarray platforms. Calls made by the different platforms and detection software are available at dbVar under nstd84.

SUBMITTER: de Ligt J

PROVIDER: S-EPMC4526866 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Platform comparison of detecting copy number variants with microarrays and whole-exome sequencing.

de Ligt Joep J Boone Philip M PM Pfundt Rolph R Vissers Lisenka E L M LE de Leeuw Nicole N Shaw Christine C Brunner Han G HG Lupski James R JR Veltman Joris A JA Hehir-Kwa Jayne Y JY

Genomics data 20141201

Copy number variation (CNV) is a common source of genetic variation that has been implicated in many genomic disorders, Mendelian diseases, and common/complex traits. Genomic microarrays are often employed for CNV detection. More recently, whole-exome sequencing (WES) has enabled detection of clinically relevant point mutations and small insertion-deletion exome wide. We evaluated (de Ligt et al. 2013) [1] the utility of short-read WES (SOLiD 5500xl) to detect clinically relevant CNVs in DNA fro ...[more]

PMID: 26258046

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Project description:BackgroundExome sequencing (ES) is a first-tier diagnostic test for many suspected Mendelian disorders. While it is routine to detect small sequence variants, it is not a standard practice in clinical settings to detect germline copy-number variants (CNVs) from ES data due to several reasons relating to performance. In this work, we comprehensively characterized one of the most sensitive ES-based CNV tools, ExomeDepth, against SNP array, a standard of care test in clinical settings to detect genome-wide CNVs.MethodsWe propose a modified ExomeDepth workflow by excluding exons with low mappability prior to variant calling to drastically reduce the false positives originating from the repetitive regions of the genome, and an iterative variant calling framework to assess the reproducibility. We used a cohort of 307 individuals with clinical ES data and clinical SNP array to estimate the sensitivity and false discovery rate of the CNV detection using exome sequencing. Further, we performed targeted testing of the STRC gene in 1972 individuals. To reduce the number of variants for downstream analysis, we performed a large-scale iterative variant calling process with random control cohorts to assess the reproducibility of the CNVs.ResultsThe modified workflow presented in this paper reduced the number of total variants identified by one third while retaining a higher sensitivity of 97% and resulted in an improved false discovery rate of 11.4% compared to the default ExomeDepth pipeline. The exclusion of exons with low mappability removes 4.5% of the exons, including a subset of exons (0.6%) in disease-associated genes which are intractable by short-read next-generation sequencing (NGS). Results from the reproducibility analysis showed that the clinically reported variants were reproducible 100% of the time and that the modified workflow can be used to rank variants from high to low confidence. Targeted testing of 30 CNVs identified in STRC, a challenging gene to ascertain by NGS, showed a 100% validation rate.ConclusionsIn summary, we introduced a modification to the default ExomeDepth workflow to reduce the false positives originating from the repetitive regions of the genome, created a large-scale iterative variant calling framework for reproducibility, and provided recommendations for implementation in clinical settings.

Dataset Information

Platform comparison of detecting copy number variants with microarrays and whole-exome sequencing.

Publications

Platform comparison of detecting copy number variants with microarrays and whole-exome sequencing.

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