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

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

On CRAN:

Conda:

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

2.00 score 3 scripts 187 downloads 9 exports 164 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK224
source / vignettesOK391
linux-release-x86_64OK236
macos-release-arm64OK238
macos-oldrel-arm64OK258
windows-develOK155
windows-releaseOK168
windows-oldrelOK151
wasm-releaseOK203

Exports:adj_CDF_logitdiff_gene_listget_example_dataHclustDepartLouvainDepartnew_scppppara_est_newqqplot_env_poisscppp

Dependencies:abindaskpassbackportsbase64encBHbitopsbroombslibcachemcaToolscheckmatecliclustercodetoolscolorspacecommonmarkcowplotcpp11crosstalkcurldata.tabledeldirdigestdoParalleldotCall64dplyrdqrngdynamicTreeCutevaluatefarverfastclusterfastDummiesfastmapfitdistrplusFNNfontawesomeforeachforeignFormulafsfuturefuture.applygenericsggplot2ggrepelggridgesglmpcaglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrHmischtmlTablehtmltoolshtmlwidgetshttpuvhttricaigraphimputeirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallifecyclelistenvlmtestmagrittrMASSMatrixmatrixStatsmemoisemimeminiUInlmennetopensslotelparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclippreprocessCoreprogressrpromisespurrrR6RANNrappdirsrbibutilsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLRdpackreshape2reticulaterlangrmarkdownROCRrpartrprojrootRSpectrarstudioapiRtsneS7sassscalesscattermoresctransformSeuratSeuratObjectshinysitmosourcetoolsspspamspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsystensortibbletidyrtidyselecttinytexutf8uwotvctrsviridisLiteWGCNAwithrxfunxtableyamlzoo

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

Rendered fromscpoissonmodel.Rmdusingknitr::rmarkdownon May 19 2026.

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