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

Genome Biology

Joseph P. Garay¹  J. S. Marron²  Siyao Liu²  Charles M. Perou²  Aatish Thennavan² 

[1] Department of Surgery, Oregon Health & Science University;Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill;

关键词: Single-cell RNA-seq;    Clustering;    Multi-scale;    Multi-resolution;    Genomics;    Reproducibility;   

DOI  :  10.1186/s13059-021-02445-5

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown