Abstract
We present DeepSomatic, the first convolutional neural network approach for somatic variant call-ing, which significantly outperforms previous techniques on different sequencing platforms, sequencing strategies, and tumor purities. DeepSomatic summarizes sequence alignments into small matrices and can incorporate more than a hundred features to capture variant signals effectively. It can be used universally as a stand-alone somatic variant caller or with an ensemble of existing callers to achieve the highest accuracy.
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.