scpoisson: Single Cell Poisson Probability Paradigm

Useful to visualize the Poissoneity (an independent Poisson statistical framework, where each RNA measurement for each cell comes from its own independent Poisson distribution) of Unique Molecular Identifier (UMI) based single cell RNA sequencing (scRNA-seq) data, and explore cell clustering based on model departure as a novel data representation.

Version: 0.0.1
Depends: R (≥ 2.10)
Imports: ggplot2, glmpca, Seurat, magrittr, dplyr, tidyr, purrr, Matrix, Rdpack, SeuratObject, WGCNA, broom, stats, methods, matrixStats
Suggests: renv, testthat (≥ 3.0.0), vdiffr, rmarkdown, knitr, qpdf
Published: 2022-08-17
Author: Yue Pan [aut, cre], Justin Landis ORCID iD [aut], Dirk Dittmer [aut], James S. Marron [aut], Di Wu [aut]
Maintainer: Yue Pan <yuep027 at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: scpoisson results

Documentation:

Reference manual: scpoisson.pdf
Vignettes: A new Poisson probability paradigm for single cell RNA-seq clustering

Downloads:

Package source: scpoisson_0.0.1.tar.gz
Windows binaries: r-devel: scpoisson_0.0.1.zip, r-release: scpoisson_0.0.1.zip, r-oldrel: scpoisson_0.0.1.zip
macOS binaries: r-release (arm64): scpoisson_0.0.1.tgz, r-oldrel (arm64): scpoisson_0.0.1.tgz, r-release (x86_64): scpoisson_0.0.1.tgz, r-oldrel (x86_64): scpoisson_0.0.1.tgz

Linking:

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