A multi-task convolutional deep neural network for variant calling in single molecule sequencing

Single Molecule Sequencing (SMS) technologies generate long but noisy reads data. Here, the authors develop Clairvoyante, a deep neural network-based method for variant calling with SMS reads such as PacBio and ONT data.

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Autores principales:	Ruibang Luo, Fritz J. Sedlazeck, Tak-Wah Lam, Michael C. Schatz
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/9ad545dd5e814a6f9351c9241b1c6be7
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spelling	oai:doaj.org-article:9ad545dd5e814a6f9351c9241b1c6be72021-12-02T16:57:43ZA multi-task convolutional deep neural network for variant calling in single molecule sequencing10.1038/s41467-019-09025-z2041-1723https://doaj.org/article/9ad545dd5e814a6f9351c9241b1c6be72019-03-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-09025-zhttps://doaj.org/toc/2041-1723Single Molecule Sequencing (SMS) technologies generate long but noisy reads data. Here, the authors develop Clairvoyante, a deep neural network-based method for variant calling with SMS reads such as PacBio and ONT data.Ruibang LuoFritz J. SedlazeckTak-Wah LamMichael C. SchatzNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-11 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Ruibang Luo Fritz J. Sedlazeck Tak-Wah Lam Michael C. Schatz A multi-task convolutional deep neural network for variant calling in single molecule sequencing
description	Single Molecule Sequencing (SMS) technologies generate long but noisy reads data. Here, the authors develop Clairvoyante, a deep neural network-based method for variant calling with SMS reads such as PacBio and ONT data.
format	article
author	Ruibang Luo Fritz J. Sedlazeck Tak-Wah Lam Michael C. Schatz
author_facet	Ruibang Luo Fritz J. Sedlazeck Tak-Wah Lam Michael C. Schatz
author_sort	Ruibang Luo
title	A multi-task convolutional deep neural network for variant calling in single molecule sequencing
title_short	A multi-task convolutional deep neural network for variant calling in single molecule sequencing
title_full	A multi-task convolutional deep neural network for variant calling in single molecule sequencing
title_fullStr	A multi-task convolutional deep neural network for variant calling in single molecule sequencing
title_full_unstemmed	A multi-task convolutional deep neural network for variant calling in single molecule sequencing
title_sort	multi-task convolutional deep neural network for variant calling in single molecule sequencing
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/9ad545dd5e814a6f9351c9241b1c6be7
work_keys_str_mv	AT ruibangluo amultitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing AT fritzjsedlazeck amultitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing AT takwahlam amultitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing AT michaelcschatz amultitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing AT ruibangluo multitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing AT fritzjsedlazeck multitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing AT takwahlam multitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing AT michaelcschatz multitaskconvolutionaldeepneuralnetworkforvariantcallinginsinglemoleculesequencing
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A multi-task convolutional deep neural network for variant calling in single molecule sequencing

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