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

Siyao LiuAatish ThennavanJoseph P GarayJ S MarronCharles M Perou
Published in: Genome biology (2021)
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.
Keyphrases
  • single cell
  • rna seq
  • high throughput
  • electronic health record
  • big data
  • genome wide
  • genetic diversity
  • stem cells
  • clinical practice
  • gene expression