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Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts

Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling, which limits their scope and generality. We propose a novel method that compares and clusters cells based on their transcript-compatibility read counts rather than on the tran...

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Autores principales: Ntranos, Vasilis, Kamath, Govinda M., Zhang, Jesse M., Pachter, Lior, Tse, David N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881296/
https://www.ncbi.nlm.nih.gov/pubmed/27230763
http://dx.doi.org/10.1186/s13059-016-0970-8
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author Ntranos, Vasilis
Kamath, Govinda M.
Zhang, Jesse M.
Pachter, Lior
Tse, David N.
author_facet Ntranos, Vasilis
Kamath, Govinda M.
Zhang, Jesse M.
Pachter, Lior
Tse, David N.
author_sort Ntranos, Vasilis
collection PubMed
description Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling, which limits their scope and generality. We propose a novel method that compares and clusters cells based on their transcript-compatibility read counts rather than on the transcript or gene quantifications used in standard analysis pipelines. In the reanalysis of two landmark yet disparate single-cell RNA-seq datasets, we show that our method is up to two orders of magnitude faster than previous approaches, provides accurate and in some cases improved results, and is directly applicable to data from a wide variety of assays. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-0970-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-48812962016-05-27 Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts Ntranos, Vasilis Kamath, Govinda M. Zhang, Jesse M. Pachter, Lior Tse, David N. Genome Biol Method Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling, which limits their scope and generality. We propose a novel method that compares and clusters cells based on their transcript-compatibility read counts rather than on the transcript or gene quantifications used in standard analysis pipelines. In the reanalysis of two landmark yet disparate single-cell RNA-seq datasets, we show that our method is up to two orders of magnitude faster than previous approaches, provides accurate and in some cases improved results, and is directly applicable to data from a wide variety of assays. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-0970-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-05-26 /pmc/articles/PMC4881296/ /pubmed/27230763 http://dx.doi.org/10.1186/s13059-016-0970-8 Text en © Ntranos et al. 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Ntranos, Vasilis
Kamath, Govinda M.
Zhang, Jesse M.
Pachter, Lior
Tse, David N.
Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
title Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
title_full Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
title_fullStr Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
title_full_unstemmed Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
title_short Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
title_sort fast and accurate single-cell rna-seq analysis by clustering of transcript-compatibility counts
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881296/
https://www.ncbi.nlm.nih.gov/pubmed/27230763
http://dx.doi.org/10.1186/s13059-016-0970-8
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