Data from: Clustering Deviation Index (CDI): A robust and accurate internal measure for evaluating scRNA-seq data clustering

Jiyuan Fang, Cliburn Chan, Kouros Owzar, Liuyang Wang, Diyuan Qin, Qi-Jing Li & Jichun Xie
The clustering of cells has been widely used to explore the heterogeneity of cell populations in single-cell RNA-sequencing (scRNA-seq). We proposed a parametric model for monoclonal and polyclonal scRNA-seq data to evaluate clustering results. Based on the parametric model, we proposed a metric (CDI) to quantify the goodness-of-fit of cell clustering to the data. Here we presented CT26.WT and T-CELL as two datasets to examine the performance of our model and metric. CT26.WT contains wild-type...
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