Benchmark and Parameter Sensitivity Analysis of Single-Cell RNA Sequencing Clustering Methods.

ABSTRACT: Single-cell RNA-seq (scRNAseq) is a powerful tool to study heterogeneity of cells. Recently, several clustering based methods have been proposed to identify distinct cell populations. These methods are based on different statistical models and usually require to perform several additional steps, such as preprocessing or dimension reduction, before applying the clustering algorithm. Individual steps are often controlled by method-specific parameters, permitting the method to be used in different modes on the same datasets, depending on the user choices. The large number of possibilities that these methods provide can intimidate non-expert users, since the available choices are not always clearly documented. In addition, to date, no large studies have invistigated the role and the impact tha

SUBMITTER: Krzak M 

PROVIDER: S-EPMC6918801 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature