DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data

Cell-type-specific genes are often strongly correlated in expression - an informative yet underexplored property of single-cell data. Here, the authors leverage gene expression correlations to develop DUBStepR, a feature selection method for accurately clustering single-cell data.

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Autores principales:	Bobby Ranjan, Wenjie Sun, Jinyu Park, Kunal Mishra, Florian Schmidt, Ronald Xie, Fatemeh Alipour, Vipul Singhal, Ignasius Joanito, Mohammad Amin Honardoost, Jacy Mei Yun Yong, Ee Tzun Koh, Khai Pang Leong, Nirmala Arul Rayan, Michelle Gek Liang Lim, Shyam Prabhakar
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/679d215e24a04b659dd516970921da96
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spelling	oai:doaj.org-article:679d215e24a04b659dd516970921da962021-12-02T19:16:20ZDUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data10.1038/s41467-021-26085-22041-1723https://doaj.org/article/679d215e24a04b659dd516970921da962021-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-26085-2https://doaj.org/toc/2041-1723Cell-type-specific genes are often strongly correlated in expression - an informative yet underexplored property of single-cell data. Here, the authors leverage gene expression correlations to develop DUBStepR, a feature selection method for accurately clustering single-cell data.Bobby RanjanWenjie SunJinyu ParkKunal MishraFlorian SchmidtRonald XieFatemeh AlipourVipul SinghalIgnasius JoanitoMohammad Amin HonardoostJacy Mei Yun YongEe Tzun KohKhai Pang LeongNirmala Arul RayanMichelle Gek Liang LimShyam PrabhakarNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Bobby Ranjan Wenjie Sun Jinyu Park Kunal Mishra Florian Schmidt Ronald Xie Fatemeh Alipour Vipul Singhal Ignasius Joanito Mohammad Amin Honardoost Jacy Mei Yun Yong Ee Tzun Koh Khai Pang Leong Nirmala Arul Rayan Michelle Gek Liang Lim Shyam Prabhakar DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data
description	Cell-type-specific genes are often strongly correlated in expression - an informative yet underexplored property of single-cell data. Here, the authors leverage gene expression correlations to develop DUBStepR, a feature selection method for accurately clustering single-cell data.
format	article
author	Bobby Ranjan Wenjie Sun Jinyu Park Kunal Mishra Florian Schmidt Ronald Xie Fatemeh Alipour Vipul Singhal Ignasius Joanito Mohammad Amin Honardoost Jacy Mei Yun Yong Ee Tzun Koh Khai Pang Leong Nirmala Arul Rayan Michelle Gek Liang Lim Shyam Prabhakar
author_facet	Bobby Ranjan Wenjie Sun Jinyu Park Kunal Mishra Florian Schmidt Ronald Xie Fatemeh Alipour Vipul Singhal Ignasius Joanito Mohammad Amin Honardoost Jacy Mei Yun Yong Ee Tzun Koh Khai Pang Leong Nirmala Arul Rayan Michelle Gek Liang Lim Shyam Prabhakar
author_sort	Bobby Ranjan
title	DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data
title_short	DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data
title_full	DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data
title_fullStr	DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data
title_full_unstemmed	DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data
title_sort	dubstepr is a scalable correlation-based feature selection method for accurately clustering single-cell data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/679d215e24a04b659dd516970921da96
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DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data

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