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DeNovoCNN: A deep learning approach to <i>de novo</i> variant calling in next generation sequencing data

2021-09-23

Abstract excerpt

<h4>ABSTRACT</h4> De novo mutations (DNMs) are an important cause of genetic disorders. The accurate identification of DNMs from sequencing data is therefore fundamental to rare disease research and diagnostics. Unfortunately, identifying reliable DNMs remains a major challenge due to sequence errors, uneven coverage, and mapping artifacts. Here, we developed a deep convolutional neural network (CNN) DNM caller (...

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Literature Corpus work: b088d6c9-83ea-59ee-8e46-049563eced9a
DOI: 10.1101/2021.09.20.461072

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