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.
Package details |
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Author | Neo Christopher Chung <nchchung@gmail.com> |
Maintainer | Neo Christopher Chung <nchchung@gmail.com> |
License | GPL-3 |
Version | 0.1.0 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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