Article

Adaptive Somatic Mutations Calls with Deep Learning and Semi-Simulated Data

2016-10-04

Abstract excerpt

<h4>ABSTRACT</h4> A number of approaches have been developed to call somatic variation in high-throughput sequencing data. Here, we present an adaptive approach to calling somatic variations. Our approach trains a deep feed-forward neural network with semi-simulated data. Semi-simulated datasets are constructed by planting somatic mutations in real datasets where no mutations are expected. Using semi-simulated da...

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Literature Corpus work: 0526ffbf-e9f7-5f20-a6af-3f40ac517219
DOI: 10.1101/079087

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