Detecting copy number variation in next generation sequencing data from diagnostic gene panels.

ABSTRACT:

Background

Detection of copy number variation (CNV) in genes associated with disease is important in genetic diagnostics, and next generation sequencing (NGS) technology provides data that can be used for CNV detection. However, CNV detection based on NGS data is in general not often used in diagnostic labs as the data analysis is challenging, especially with data from targeted gene panels. Wet lab methods like MLPA (MRC Holland) are widely used, but are expensive, time consuming and have gene-specific limitations. Our aim has been to develop a bioinformatic tool for CNV detection from NGS data in medical genetic diagnostic samples.

Results

Our computational pipeline for detection of CNVs in NGS data from targeted gene panels utilizes coverage depth of the captured regions a

SUBMITTER: Singh AK 

PROVIDER: S-EPMC8406611 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature