ASCOT identifies key regulators of neuronal subtype-specific splicing

The increasing amount of raw RNA-seq data calls for new computational methods to mine information. Here, the authors present ASCOT, a computational resource to identify splice variants in RNA-seq data, and apply it to splicing patterns in neurons and unique splicing patterns in rod photoreceptors.

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Autores principales:	Jonathan P. Ling, Christopher Wilks, Rone Charles, Patrick J. Leavey, Devlina Ghosh, Lizhi Jiang, Clayton P. Santiago, Bo Pang, Anand Venkataraman, Brian S. Clark, Abhinav Nellore, Ben Langmead, Seth Blackshaw
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/7ea8584150d14155b401fb552d0229f2
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spelling	oai:doaj.org-article:7ea8584150d14155b401fb552d0229f22021-12-02T15:39:08ZASCOT identifies key regulators of neuronal subtype-specific splicing10.1038/s41467-019-14020-52041-1723https://doaj.org/article/7ea8584150d14155b401fb552d0229f22020-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-14020-5https://doaj.org/toc/2041-1723The increasing amount of raw RNA-seq data calls for new computational methods to mine information. Here, the authors present ASCOT, a computational resource to identify splice variants in RNA-seq data, and apply it to splicing patterns in neurons and unique splicing patterns in rod photoreceptors.Jonathan P. LingChristopher WilksRone CharlesPatrick J. LeaveyDevlina GhoshLizhi JiangClayton P. SantiagoBo PangAnand VenkataramanBrian S. ClarkAbhinav NelloreBen LangmeadSeth BlackshawNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-12 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jonathan P. Ling Christopher Wilks Rone Charles Patrick J. Leavey Devlina Ghosh Lizhi Jiang Clayton P. Santiago Bo Pang Anand Venkataraman Brian S. Clark Abhinav Nellore Ben Langmead Seth Blackshaw ASCOT identifies key regulators of neuronal subtype-specific splicing
description	The increasing amount of raw RNA-seq data calls for new computational methods to mine information. Here, the authors present ASCOT, a computational resource to identify splice variants in RNA-seq data, and apply it to splicing patterns in neurons and unique splicing patterns in rod photoreceptors.
format	article
author	Jonathan P. Ling Christopher Wilks Rone Charles Patrick J. Leavey Devlina Ghosh Lizhi Jiang Clayton P. Santiago Bo Pang Anand Venkataraman Brian S. Clark Abhinav Nellore Ben Langmead Seth Blackshaw
author_facet	Jonathan P. Ling Christopher Wilks Rone Charles Patrick J. Leavey Devlina Ghosh Lizhi Jiang Clayton P. Santiago Bo Pang Anand Venkataraman Brian S. Clark Abhinav Nellore Ben Langmead Seth Blackshaw
author_sort	Jonathan P. Ling
title	ASCOT identifies key regulators of neuronal subtype-specific splicing
title_short	ASCOT identifies key regulators of neuronal subtype-specific splicing
title_full	ASCOT identifies key regulators of neuronal subtype-specific splicing
title_fullStr	ASCOT identifies key regulators of neuronal subtype-specific splicing
title_full_unstemmed	ASCOT identifies key regulators of neuronal subtype-specific splicing
title_sort	ascot identifies key regulators of neuronal subtype-specific splicing
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/7ea8584150d14155b401fb552d0229f2
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ASCOT identifies key regulators of neuronal subtype-specific splicing

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