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MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data
Single-cell RNA sequencing (scRNA-seq) provides new opportunities to characterize cell populations, typically accomplished through some type of clustering analysis. Estimation of the optimal cluster number (K) is a crucial step but often ignored. Our approach improves most current scRNA-seq cluster...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8375188/ https://www.ncbi.nlm.nih.gov/pubmed/34412669 http://dx.doi.org/10.1186/s13059-021-02445-5 |
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author | Liu, Siyao Thennavan, Aatish Garay, Joseph P. Marron, J. S. Perou, Charles M. |
author_facet | Liu, Siyao Thennavan, Aatish Garay, Joseph P. Marron, J. S. Perou, Charles M. |
author_sort | Liu, Siyao |
collection | PubMed |
description | Single-cell RNA sequencing (scRNA-seq) provides new opportunities to characterize cell populations, typically accomplished through some type of clustering analysis. Estimation of the optimal cluster number (K) is a crucial step but often ignored. Our approach improves most current scRNA-seq cluster methods by providing an objective estimation of the number of groups using a multi-resolution perspective. MultiK is a tool for objective selection of insightful Ks and achieves high robustness through a consensus clustering approach. We demonstrate that MultiK identifies reproducible groups in scRNA-seq data, thus providing an objective means to estimating the number of possible groups or cell-type populations present. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02445-5. |
format | Online Article Text |
id | pubmed-8375188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83751882021-08-23 MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data Liu, Siyao Thennavan, Aatish Garay, Joseph P. Marron, J. S. Perou, Charles M. Genome Biol Method Single-cell RNA sequencing (scRNA-seq) provides new opportunities to characterize cell populations, typically accomplished through some type of clustering analysis. Estimation of the optimal cluster number (K) is a crucial step but often ignored. Our approach improves most current scRNA-seq cluster methods by providing an objective estimation of the number of groups using a multi-resolution perspective. MultiK is a tool for objective selection of insightful Ks and achieves high robustness through a consensus clustering approach. We demonstrate that MultiK identifies reproducible groups in scRNA-seq data, thus providing an objective means to estimating the number of possible groups or cell-type populations present. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02445-5. BioMed Central 2021-08-19 /pmc/articles/PMC8375188/ /pubmed/34412669 http://dx.doi.org/10.1186/s13059-021-02445-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Method Liu, Siyao Thennavan, Aatish Garay, Joseph P. Marron, J. S. Perou, Charles M. MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data |
title | MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data |
title_full | MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data |
title_fullStr | MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data |
title_full_unstemmed | MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data |
title_short | MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data |
title_sort | multik: an automated tool to determine optimal cluster numbers in single-cell rna sequencing data |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8375188/ https://www.ncbi.nlm.nih.gov/pubmed/34412669 http://dx.doi.org/10.1186/s13059-021-02445-5 |
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