Improving CNV Detection Performance in Microarray Data Using a Machine Learning-Based Approach.

ABSTRACT: Copy number variation (CNV) is a primary source of structural variation in the human genome, leading to several disorders. Therefore, analyzing neonatal CNVs is crucial for managing CNV-related chromosomal disabilities. However, genomic waves can hinder accurate CNV analysis. To mitigate the influences of the waves, we adopted a machine learning approach and developed a new method that uses a modified log R ratio instead of the commonly used log R ratio. Validation results using samples with known CNVs demonstrated the superior performance of our method. We analyzed a total of 16,046 Korean newborn samples using the new method and identified CNVs related to 39 genetic disorders were identified in 342 cases. The most frequently detected CNV-related disorder was Joubert syndrome 4. The accur

SUBMITTER: Goh CJ 

PROVIDER: S-EPMC10871075 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature