Package: scpoisson 0.0.1

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_0.0.1.tar.gz
scpoisson_0.0.1.zip(r-4.5)scpoisson_0.0.1.zip(r-4.4)scpoisson_0.0.1.zip(r-4.3)
scpoisson_0.0.1.tgz(r-4.4-any)scpoisson_0.0.1.tgz(r-4.3-any)
scpoisson_0.0.1.tar.gz(r-4.5-noble)scpoisson_0.0.1.tar.gz(r-4.4-noble)
scpoisson_0.0.1.tgz(r-4.4-emscripten)scpoisson_0.0.1.tgz(r-4.3-emscripten)
scpoisson.pdf |scpoisson.html✨
scpoisson/json (API)
NEWS

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

Peer review:

On CRAN:

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

2.70 score 4 scripts 132 downloads 8 exports 187 dependencies

Last updated 2 years agofrom:b2c15f1caa. Checks:OK: 3 NOTE: 3 ERROR: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 29 2024
R-4.5-winERROROct 29 2024
R-4.5-linuxNOTEOct 29 2024
R-4.4-winNOTEOct 29 2024
R-4.4-macNOTEOct 29 2024
R-4.3-winOKOct 29 2024
R-4.3-macOKOct 29 2024

Exports:adj_CDF_logitdiff_gene_listget_example_dataHclustDepartLouvainDepartpara_est_newqqplot_env_poisscppp

Dependencies:abindAnnotationDbiaskpassbackportsbase64encBHBiobaseBiocGenericsBiostringsbitbit64bitopsblobbroombslibcachemcaToolscheckmatecliclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDBIdeldirdigestdoParalleldotCall64dplyrdqrngdynamicTreeCutevaluatefansifarverfastclusterfastDummiesfastmapfitdistrplusFNNfontawesomeforeachforeignFormulafsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataggplot2ggrepelggridgesglmpcaglobalsglueGO.dbgoftestgplotsgridExtragtablegtoolsherehighrHmischtmlTablehtmltoolshtmlwidgetshttpuvhttricaigraphimputeIRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglaterlatticelazyevalleidenlifecyclelistenvlmtestmagrittrMASSMatrixmatrixStatsmemoisemgcvmimeminiUImunsellnlmennetopensslparallellypatchworkpbapplypillarpkgconfigplogrplotlyplyrpngpolyclippreprocessCoreprogressrpromisespurrrR6RANNrappdirsrbibutilsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLRdpackreshape2reticulaterlangrmarkdownROCRrpartrprojrootRSpectraRSQLiterstudioapiRtsneS4VectorssassscalesscattermoresctransformSeuratSeuratObjectshinysitmosourcetoolsspspamspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsystensortibbletidyrtidyselecttinytexUCSC.utilsutf8uwotvctrsviridisviridisLiteWGCNAwithrxfunxtableXVectoryamlzlibbioczoo

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

Yue Pan

Rendered fromscpoissonmodel.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2022-08-17
Started: 2022-08-17