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.
CITATION STYLE
Liu, S., Thennavan, A., Garay, J. P., Marron, J. S., & Perou, C. M. (2021). MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data. Genome Biology, 22(1). https://doi.org/10.1186/s13059-021-02445-5
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