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Evaluation of the performance of copy number variant prediction tools for the detection of deletions from whole genome sequencing data.

08:00 EDT 6th April 2019 | BioPortfolio

Summary of "Evaluation of the performance of copy number variant prediction tools for the detection of deletions from whole genome sequencing data."

Whole genome sequencing (WGS) has increased in popularity and decreased in cost over the past decade, rendering this approach as a viable and sensitive method for variant detection. In addition to its utility for single nucleotide variant detection, WGS data has the potential to detect Copy Number Variants (CNV) to fine resolution. Many CNV detection software packages have been developed exploiting four main types of data: read pair, split read, read depth, and assembly based methods. The aim of this study was to evaluate the efficiency of each of these main approaches in detecting germline deletions.

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This article was published in the following journal.

Name: Journal of biomedical informatics
ISSN: 1532-0480
Pages: 103174

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