Whole-genome sequencing analysis of CNV using low-coverage and paired-end strategies is efficient and outperforms array-based CNV analysis

Stanford researchers show that whole-genome sequencing (WGS) can replace microarrays for detecting copy-number variants (CNVs) in the human genome – by sequencing the samples at low coverage using benchtop next-generation DNA sequencers. Microarrays are the current standard for CNV detection in clinical diagnostics for birth defects, brain disorders, or cancer, and also in stem cell culture QC.  While deep WGS offers the most comprehensive genome analysis, it is still relatively expensive and has turnaround times too long for clinical or QC needs. This new study reveals that low-coverage WGS easily outperforms microarrays in detecting CNVs while offering the same short turnaround times and moderate costs. (By Dr. Bo Zhou, https://jmg.bmj.com/content/early/2018/07/30/jmedgenet-2018-105272 )

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