Efficient detection of copy‐number variations using exome data: Batch‐ and sex‐based analyses

Abstract

Many algorithms to detect copy number variations (CNVs) using exome sequencing (ES) data have been reported and evaluated on their sensitivity and specificity, reproducibility, and precision. However, operational optimization of such algorithms for a better performance has not been fully addressed. ES of 1199 samples including 763 patients with different disease profiles was performed. ES data were analyzed to detect CNVs by both the eXome Hidden Markov Model (XHMM) and modified Nord's method. To efficiently detect rare CNVs, we aimed to decrease sequencing biases by analyzing, at the same time, the data of all unrelated samples sequenced in the same flow cell as a batch, and to eliminate sex effects of X-linked CNVs by analyzing female and male sequences separately. We also applied several filtering steps for more efficient CNV selection. The average number of CNVs detected in one sample was <5. This optimization together with targeted CNV analysis by Nord's method identified pathogenic/likely pathogenic CNVs in 34 patients (4.5%, 34/763). In particular, among 142 patients with epilepsy, the current protocol detected clinically relevant CNVs in 19 (13.4%) patients, whereas the previous protocol identified them in only 14 (9.9%) patients. Thus, this batch-based XHMM analysis efficiently selected rare pathogenic CNVs in genetic diseases.

Clinical course of a Japanese patient with developmental delay linked to a small 6q16.1 deletion

“…The examination protocols were approved by the Central Ethics Committee of Tohoku University School of Medicine Hospital (2018–2-216). Exome sequencing data were analyzed using the eXome Hidden Markov Model (XHMM) and modified Nord’s method 5 . We detected the 6q16.1 deletion (chr6: 99282717–100062596) (hg19) (Fig.…”

Long-term course of early onset developmental and epileptic encephalopathy associated with 2q24.3 microduplication

“…The high resolution chromosomal microarray approach has discovered novel rare DNA CNVs across the genome and identified many causative genes. WES has recently been applied to detecting CNVs by both XHMM and Nord’s method using WES data [17] , [18] . This approach appears useful to increase diagnostic yield to identify genetic causes of epilepsy, as in this case.…”

An integrated genetic analysis of epileptogenic brain malformed lesions

“…To detect somatic CNVs, we analyzed WES data using the eXome-Hidden Markov Model (XHMM) [22,34] and/or the SNP array with CytoScan HD array (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer's instructions. CNVs were confirmed using the SNP array for patients F43 and F70 and droplet digital PCR (ddPCR) for patient F30.…”