The algorithmic detection of cancer-associated variants can be accelerated by leveraging machine-learning classifiers to filter out reads matched to pan-genome k-mer sets.
This is a preview of subscription content, access via your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$79.00 per year
only $6.58 per issue
Rent or buy this article
Get just this article for as long as you need it
Prices may be subject to local taxes which are calculated during checkout
Mullin, E. The era of fast, cheap genome sequencing is here. Wired https://go.nature.com/3ofIjRH (2022).
Sohn, J.-I. et al. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-022-00980-5 (2022).
Wang, T. et al. Nature 604, 437–446 (2022).
Mahmoud, M. et al. Genome Biol. 20, 246 (2019).
Salamat, S. & Rosing, T. Preprint at https://arxiv.org/abs/2002.02394 (2020).
Almogy, G. et al. Preprint at bioRxiv https://doi.org/10.1101/2022.05.29.493900 (2022).
Cheng, A. P. et al. Preprint at bioRxiv https://doi.org/10.1101/2022.11.17.516904 (2022).
Duncavage, E. J. et al. N. Engl. J. Med. 384, 924–935 (2021).
Shukla, N. et al. Nat. Commun. 13, 2485 (2022).
Li, Y. et al. Nature 578, 112–121 (2020).
Hadi, K. et al. Cell 183, 197–210.e32 (2020).
M.I. is an advisor to ImmPACT Bio.
Rights and permissions
About this article
Cite this article
Choo, ZN., Imieliński, M. Faster detection of somatic structural variants. Nat. Biomed. Eng (2023). https://doi.org/10.1038/s41551-023-01039-9