A robust model for read count data in exome sequencing experiments and implications for copy number variant calling

Abstract

Motivation: Exome sequencing has proven to be an effective tool to discover the genetic basis of Mendelian disorders. It is well established that copy number variants (CNVs) contribute to the etiology of these disorders. However, calling CNVs from exome sequence data is challenging. A typical read depth strategy consists of using another sample (or a combination of samples) as a reference to control for the variability at the capture and sequencing steps. However, technical variability between samples complicates the analysis and can create spurious CNV calls.Results: Here, we introduce ExomeDepth, a new CNV calling algorithm designed to control for this technical variability. ExomeDepth uses a robust model for the read count data and uses this model to build an optimized reference set in order to maximize the power to detect CNVs. As a result, ExomeDepth is effective across a wider range of exome datasets than the previously existing tools, even for small (e.g. one to two exons) and heterozygous deletions. We used this new approach to analyse exome data from 24 patients with primary immunodeficiencies. Depending on data quality and the exact target region, we find between 170 and 250 exonic CNV calls per sample. Our analysis identified two novel causative deletions in the genes GATA2 and DOCK8.Availability: The code used in this analysis has been implemented into an R package called ExomeDepth and is available at the Comprehensive R Archive Network (CRAN).Contact: v.plagnol@ucl.ac.ukSupplementary Information: Supplementary data are available at Bioinformatics online.

The use of next-generation sequencing in clinical diagnosis of familial hypercholesterolemia

“…The detection of large variants from NGS data has been shown previously, but its use in FH diagnostics has not yet been investigated. 20,21 Here, the combination of SureSelect Target Enrichment System/ HiSeq and data analysis using ExomeDepth software 18 led to correct identification of all eight large deletions and one large duplication. This shows the potential of using hybrid capture for the detection of both short and large sequence variants in FH.…”

“…A read depth-based method, 18 as implemented in R package ExomeDepth, was used to identify deletions and duplications spanning at least one exon. Each sequencing batch of samples was processed separately to increase the quality of a reference set for each sample and therefore to maximize the power to detect CNVs.…”

Whole exome sequencing identifies genetic variants in inherited thrombocytopenia with secondary qualitative function defects

“…18 The analysis revealed an average of 137 copy number variations per exome (n=32). No copy number variations were deemed potential candidates either because of a high allele frequency or a lack of expression or functional role of the gene within the megakaryocyte/platelet lineage.…”

Detection of genomic rearrangements from targeted resequencing data in Parkinson's disease patients

“…Notably, the recent advent of the NGS technologies has been accompanied by the implementation of new bioinformatic tools to detect copy number variants (CNVs) from the depth of read mapping, even after applying specific targeted enrichment 3, 4, 5, 6, 7. Most of these new tools are based on the assumption that differences in the depth of coverage among specific genomic regions and across multiple samples can be used as an indicator of the relative number of copies, resulting in a semiquantitative estimation of CNVs.…”