Hyun Kim, MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing datamics data with TDEseq

In this talk, we discuss the paper, “MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data” by Siyao Liu et.al.  Genome Biology, 2024.

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.