Evaluate cell identities estimated from clustering of scRNA-seq data in the Seurat pipeline. This package provides new functionalities that can be used with a Seurat object. K-means clustering is enhanced with the Kmeans++ initialization for faster convergence and the mini-batch algorithm that can easily scale to millions of single cells. Cell identities that are determined by clustering algorithms are evaluated by the jackstraw methods, providing p-values and posterior inclusion probabilities (PIPs) for individual single cells. These probabilities can be used for feature selection and visualization. In particular, t-SNE projection is improved by hard- or soft-thresholding with PIPs or adjusted p-values.
|Author||Neo Christopher Chung <[email protected]>|
|Maintainer||Neo Christopher Chung <[email protected]>|
|Package repository||View on GitHub|
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