
==== Front
bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.08.16.608331
preprint
1
Article
DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies
Park Jimin http://orcid.org/0000-0002-4702-382X

Cook Daniel E. http://orcid.org/0000-0003-3347-562X

Chang Pi-Chuan http://orcid.org/0000-0003-3021-6446

Kolesnikov Alexey
Brambrink Lucas
Mier Juan Carlos http://orcid.org/0009-0002-5189-5337

Gardner Joshua http://orcid.org/0000-0003-4386-0628

McNulty Brandy
Sacco Samuel
Keskus Ayse
Bryant Asher
Ahmad Tanveer
Shetty Jyoti
Zhao Yongmei
Tran Bao
Narzisi Giuseppe http://orcid.org/0000-0003-1118-8849

Helland Adrienne
Yoo Byunggil
Pushel Irina
Lansdon Lisa A.
Bi Chengpeng
Walter Adam
Gibson Margaret
Pastinen Tomi
Farooqi Midhat S. http://orcid.org/0000-0002-5238-1349

Robine Nicolas
Miga Karen H.
Carroll Andrew http://orcid.org/0000-0002-4824-6689

Kolmogorov Mikhail
Paten Benedict http://orcid.org/0000-0001-8863-3539

Shafin Kishwar http://orcid.org/0000-0001-5252-3434

19 8 2024
2024.08.16.608331https://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
http://biorxiv.org/lookup/doi/10.1101/2024.08.16.608331
nihpp-2024.08.16.608331.pdf
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.
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pmc
