MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data

MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data

Abstract 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...

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Bibliographic Details
Main Authors: Siyao Liu, Aatish Thennavan, Joseph P. Garay, J. S. Marron, Charles M. Perou
Format: Article
Language:English
Published: BMC 2021-08-01
Series:Genome Biology
Subjects:
Single-cell RNA-seq
Clustering
Multi-scale
Multi-resolution
Genomics
Reproducibility
Online Access:https://doi.org/10.1186/s13059-021-02445-5
Description
Summary:Abstract 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.
ISSN:1474-760X

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