Human Pangenome Reference Consortium (@humanpangenome.bsky.social)

DeepSomatic is a deep learning method that detects somatic SNVs and indels from both short-read and long-read sequencing data. It supports whole-genome and exome sequencing and is compatible with tumor-normal, tumor-only, and FFPE-prepared samples. www.biorxiv.org/content/10.1...

loading . . .

DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies Somatic variant detection is an integral part of cancer genomics analysis. While most methods have focused on short-read sequencing, long-read technologies now offer potential advantages in terms of repeat mapping and variant phasing. We present DeepSomatic, a deep learning method for detecting somatic SNVs and insertions and deletions (indels) from both short-read and long-read data, with modes for whole-genome and exome sequencing, and able to run on tumor-normal, tumor-only, and with FFPE-prepared samples. To help address the dearth of publicly available training and benchmarking data for somatic variant detection, we generated and make openly available a dataset of five matched tumor-normal cell line pairs sequenced with Illumina, PacBio HiFi, and Oxford Nanopore Technologies, along with benchmark variant sets. Across samples and technologies (short-read and long-read), DeepSomatic consistently outperforms existing callers, particularly for indels. ### Competing Interest Statement K.S., D.E.C., P.C., A. Kolesnikov, L.B., J.C.M., and A.C. are employees of Google LLC and own Alphabet stock as part of the standard compensation package. M.S.F. is a part of the speakers bureau for Bayer and PacBio. https://www.biorxiv.org/content/10.1101/2024.08.16.608331v1.full