Robustness in single cell clustering

In recent years, the analysis of single cell RNA-sequencing (scRNA-seq) technology has been increasing. Although scRNA-seq is a powerful approach to studying the heterogene- ity of cells bringing an increasing number of discoveries in biomedical research, the analysis of such data is still challenging. To decipher the unknown cell heterogeneity in single-cell transcriptomic data, clustering approaches help to find subpopulations of cells based on their similarity in the gene expression profiles. Since there are many clustering methods, in this work we present an algorithm for the validation of the clustering to determine how well clusters approximate cell sub-types.