Package: scpoisson 0.0.2

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.

Authors:Yue Pan [aut, cre], Justin Landis [aut], Dirk Dittmer [aut], James S. Marron [aut], Di Wu [aut]

scpoisson_0.0.2.tar.gz
scpoisson_0.0.2.zip(r-4.7-any)scpoisson_0.0.2.zip(r-4.6-any)scpoisson_0.0.2.zip(r-4.5-any)
scpoisson_0.0.2.tgz(r-4.6-any)scpoisson_0.0.2.tgz(r-4.5-any)
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scpoisson_0.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
scpoisson/json (API)

# Install 'scpoisson' in R:

install.packages('scpoisson', repos = c('https://yuepan027.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 4 scripts 330 downloads 9 exports 165 dependencies

Last updated from:23486c0ba9. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	250
source / vignettes	OK	365
linux-release	OK	255
macos-release	OK	202
macos-oldrel	OK	211
windows-devel	OK	141
windows-release	OK	172
windows-oldrel	OK	146
wasm-release	OK	141

Exports:adj_CDF_logit diff_gene_list get_example_data HclustDepart LouvainDepart new_scppp para_est_new qqplot_env_pois scppp

Dependencies:abind askpass backports base64enc BH bitops broom bslib cachem caTools checkmate cli cluster codetools colorspace commonmark cowplot cpp11 crosstalk curl data.table deldir digest doParallel dotCall64 dplyr dqrng dynamicTreeCut evaluate farver fastcluster fastDummies fastmap fitdistrplus FNN fontawesome foreach foreign Formula fs future future.apply generics ggplot2 ggrepel ggridges glmpca globals glue goftest gplots gridExtra gtable gtools here highr Hmisc htmlTable htmltools htmlwidgets httpuv httr ica igraph impute irlba isoband iterators jquerylib jsonlite KernSmooth knitr labeling later lattice lazyeval lifecycle listenv lmtest magrittr MASS Matrix matrixStats memoise mime miniUI nlme nnet openssl otel parallelly patchwork pbapply pillar pkgconfig plotly plyr png polyclip preprocessCore progressr promises purrr R6 RANN rappdirs rbibutils RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppHNSW RcppProgress RcppThread RcppTOML Rdpack reshape2 reticulate rlang rmarkdown ROCR rpart rprojroot RSpectra rstudioapi Rtsne S7 sass scales scattermore sctransform Seurat SeuratObject shiny sitmo sourcetools sp spam spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar spatstat.utils stringi stringr survival sys tensor tibble tidyr tidyselect tinytex utf8 uwot vctrs viridisLite WGCNA withr xfun xtable yaml zoo

A new Poisson probability paradigm for single cell RNA-seq clustering

Introduction | Installing | Poissoneity of scRNA-seq data | Cell clustering based on model departure | References

Rendered fromscpoissonmodel.Rmdusingknitr::rmarkdown

Last update: 2025-12-20
Started: 2022-08-17

Help page	Topics
A novel data representation based on Poisson probability	adj_CDF_logit adj_CDF_logit.matrix adj_CDF_logit.scppp
Cluster label clean	clust_clean
Cluster size	cluster_size
Differential expression analysis	diff_gene_list diff_gene_list.matrix diff_gene_list.scppp
get FWER cutoffs for shc object	fwer_cutoff-shc fwer_cutoff.shc
get example data	get_example_data
Cluster cells in a recursive way	HclustDepart HclustDepart.matrix HclustDepart.scppp
Linear interpolation for one sample given reference sample	interpolate
Logit transformation	logit
Louvain clustering using departure as data representation	LouvainDepart LouvainDepart.matrix LouvainDepart.scppp
Random sample generation function to generate sets of samples from theoretical Poisson distribution.	nboot_small
A more "continuous" approximation of quantiles of samples with a few integer case	new_quantile
A more "continuous" approximation of quantiles from the theoretical Poisson distribution.	new_quantile_pois
Generate New scppp object	new_scppp
Parameter estimates based on two-way approximation	para_est_new
Print scppp objects	print.scppp
Paired quantile after interpolation between two samples	qq_interpolation
Q-Q plot comparing samples with a theoretical Poisson distribution	qqplot_env_pois qqplot_env_pois.scppp
Q-Q plot comparing two samples with small discrete counts	qqplot_small_test
Generate New scppp object	scppp
Significance for first split using sigclust2	sigp
Dirk theme ggplots	theme_dirk

Package: scpoisson 0.0.2

scpoisson: Single Cell Poisson Probability Paradigm

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Help Manual

Usage by other packages (reverse dependencies)