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bioRxiv · 10.1101/2020.04.13.039016

CNV-PG: a machine-learning framework for accurate copy number variation predicting and genotyping

Wang, T.·Sun, J.·Zhang, X.·Wang, W.-J.·Zhou, Q.
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Abstract

MotivationCopy-number variants (CNVs) are one of the major causes of genetic disorders. However, current methods for CNV calling have high false-positive rates and low concordance, and a few of them can accurately genotype CNVs. ResultsHere we propose CNV-PG (CNV Predicting and Genotyping), a machine-learning framework for accurately predicting and genotyping CNVs from paired-end sequencing data. CNV-PG can efficiently remove false positive CNVs from existing CNV discovery algorithms, and integrate CNVs from multiple CNV callers into a unified call set with high genotyping accuracy. AvailabilityCNV-PG is available at https://github.com/wonderful1/CNV-PG

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Wang, T., Sun, J., Zhang, X., Wang, W.-J., Zhou, Q.. 2020-04-14. CNV-PG: a machine-learning framework for accurate copy number variation predicting and genotyping. https://doi.org/10.1101/2020.04.13.039016

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