High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.

Saved in:
Bibliographic Details
Title: High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.
Authors: Liao H; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Conwill A; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Light-Maka I; Max Planck Institute for Infection Biology; Berlin 10117, Germany.; Charité-Universitätsmedizin Berlin, Berlin 10117, Germany., Fenk M; Max Planck Institute for Infection Biology; Berlin 10117, Germany.; Humboldt-Universität zu Berlin, Faculty of Life Sciences, Berlin, Germany., Mitchell AH; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Qu EB; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Torrillo P; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Baker JS; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Key FM; Max Planck Institute for Infection Biology; Berlin 10117, Germany., Lieberman TD; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA.; Ragon Institute of MGH, MIT, and Harvard; Cambridge, MA 02139, USA.
Source: BioRxiv : the preprint server for biology [bioRxiv] 2025 Sep 29. Date of Electronic Publication: 2025 Sep 29.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2692-8205
DOI:10.1101/2025.09.26.678787