A collection of tools for cancer single cell RNA-seq analysis. Cell clustering and feature gene selection analysis employ maximum likelihood and Bayesian non-negative matrix factorization algorithm. Input data set consists of RNA count matrix, gene, and cell bar code annotations. Analysis outputs are factor matrices for multiple ranks, quality measures (maximum likelihood) or evidence (Bayesian) with respect to rank. The package includes utilities for downstream analyses, including meta-gene identification, visualization, and construction of rank-based trees for cell clusters.
|Bioconductor views||Bayesian Clustering SingleCell Transcriptomics|
|License||GPL (>= 2)|
|Package repository||View on GitHub|
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