ScMelody: An Enhanced Consensus-Based Clustering Model for Single-Cell Methylation Data by Reconstructing Cell-to-Cell Similarity.

ABSTRACT: Single-cell DNA methylation sequencing technology has brought new perspectives to investigate epigenetic heterogeneity, supporting a need for computational methods to cluster cells based on single-cell methylation profiles. Although several methods have been developed, most of them cluster cells based on single (dis)similarity measures, failing to capture complete cell heterogeneity and resulting in locally optimal solutions. Here, we present scMelody, which utilizes an enhanced consensus-based clustering model to reconstruct cell-to-cell methylation similarity patterns and identifies cell subpopulations with the leveraged information from multiple basic similarity measures. Besides, benefitted from the reconstructed cell-to-cell similarity measure, scMelody could conveniently leverage the

SUBMITTER: Tian Q 

PROVIDER: S-EPMC8905497 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature