SC3 - consensus clustering of single-cell RNA-Seq data

Single-cell RNA-seq (scRNA-seq) enables a quantitative cell-type characterisation based on global transcriptome profiles. We present Single-Cell Consensus Clustering (SC3), a user-friendly tool for unsupervised clustering which achieves high accuracy and robustness by combining multiple clustering s...

Descripción completa

Detalles Bibliográficos
Autores principales: Kiselev, Vladimir Yu., Kirschner, Kristina, Schaub, Michael T., Andrews, Tallulah, Yiu, Andrew, Chandra, Tamir, Natarajan, Kedar N, Reik, Wolf, Barahona, Mauricio, Green, Anthony R, Hemberg, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5410170/
https://www.ncbi.nlm.nih.gov/pubmed/28346451
http://dx.doi.org/10.1038/nmeth.4236
_version_ 1783232623651323904
author Kiselev, Vladimir Yu.
Kirschner, Kristina
Schaub, Michael T.
Andrews, Tallulah
Yiu, Andrew
Chandra, Tamir
Natarajan, Kedar N
Reik, Wolf
Barahona, Mauricio
Green, Anthony R
Hemberg, Martin
author_facet Kiselev, Vladimir Yu.
Kirschner, Kristina
Schaub, Michael T.
Andrews, Tallulah
Yiu, Andrew
Chandra, Tamir
Natarajan, Kedar N
Reik, Wolf
Barahona, Mauricio
Green, Anthony R
Hemberg, Martin
author_sort Kiselev, Vladimir Yu.
collection PubMed
description Single-cell RNA-seq (scRNA-seq) enables a quantitative cell-type characterisation based on global transcriptome profiles. We present Single-Cell Consensus Clustering (SC3), a user-friendly tool for unsupervised clustering which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach. We demonstrate that SC3 is capable of identifying subclones based on the transcriptomes from neoplastic cells collected from patients.
format Online
Article
Text
id pubmed-5410170
institution National Center for Biotechnology Information
language English
publishDate 2017
record_format MEDLINE/PubMed
spelling pubmed-54101702017-09-27 SC3 - consensus clustering of single-cell RNA-Seq data Kiselev, Vladimir Yu. Kirschner, Kristina Schaub, Michael T. Andrews, Tallulah Yiu, Andrew Chandra, Tamir Natarajan, Kedar N Reik, Wolf Barahona, Mauricio Green, Anthony R Hemberg, Martin Nat Methods Article Single-cell RNA-seq (scRNA-seq) enables a quantitative cell-type characterisation based on global transcriptome profiles. We present Single-Cell Consensus Clustering (SC3), a user-friendly tool for unsupervised clustering which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach. We demonstrate that SC3 is capable of identifying subclones based on the transcriptomes from neoplastic cells collected from patients. 2017-03-27 2017-05 /pmc/articles/PMC5410170/ /pubmed/28346451 http://dx.doi.org/10.1038/nmeth.4236 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Kiselev, Vladimir Yu.
Kirschner, Kristina
Schaub, Michael T.
Andrews, Tallulah
Yiu, Andrew
Chandra, Tamir
Natarajan, Kedar N
Reik, Wolf
Barahona, Mauricio
Green, Anthony R
Hemberg, Martin
SC3 - consensus clustering of single-cell RNA-Seq data
title SC3 - consensus clustering of single-cell RNA-Seq data
title_full SC3 - consensus clustering of single-cell RNA-Seq data
title_fullStr SC3 - consensus clustering of single-cell RNA-Seq data
title_full_unstemmed SC3 - consensus clustering of single-cell RNA-Seq data
title_short SC3 - consensus clustering of single-cell RNA-Seq data
title_sort sc3 - consensus clustering of single-cell rna-seq data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5410170/
https://www.ncbi.nlm.nih.gov/pubmed/28346451
http://dx.doi.org/10.1038/nmeth.4236
work_keys_str_mv AT kiselevvladimiryu sc3consensusclusteringofsinglecellrnaseqdata
AT kirschnerkristina sc3consensusclusteringofsinglecellrnaseqdata
AT schaubmichaelt sc3consensusclusteringofsinglecellrnaseqdata
AT andrewstallulah sc3consensusclusteringofsinglecellrnaseqdata
AT yiuandrew sc3consensusclusteringofsinglecellrnaseqdata
AT chandratamir sc3consensusclusteringofsinglecellrnaseqdata
AT natarajankedarn sc3consensusclusteringofsinglecellrnaseqdata
AT reikwolf sc3consensusclusteringofsinglecellrnaseqdata
AT barahonamauricio sc3consensusclusteringofsinglecellrnaseqdata
AT greenanthonyr sc3consensusclusteringofsinglecellrnaseqdata
AT hembergmartin sc3consensusclusteringofsinglecellrnaseqdata

Ejemplares similares