Package: nebula 1.5.3

nebula: Negative Binomial Mixed Models Using Large-Sample Approximation for Differential Expression Analysis of ScRNA-Seq Data

A fast negative binomial mixed model for conducting association analysis of multi-subject single-cell data. It can be used for identifying marker genes, differential expression and co-expression analyses. The model includes subject-level random effects to account for the hierarchical structure in multi-subject single-cell data. See He et al. (2021) <doi:10.1038/s42003-021-02146-6>.

Authors:Liang He [aut, cre], Raghav Sharma [ctb]

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nebula/json (API)

# Install 'nebula' in R:
install.packages('nebula', repos = c('https://lhe17.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lhe17/nebula/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda-Forge:

cpp

6.40 score 35 stars 145 scripts 269 downloads 4 exports 172 dependencies

Last updated 1 years agofrom:e17fb830b6. Checks:1 OK, 10 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 09 2025
R-4.5-win-x86_64NOTEFeb 09 2025
R-4.5-mac-x86_64NOTEFeb 09 2025
R-4.5-mac-aarch64NOTEFeb 09 2025
R-4.5-linux-x86_64NOTEFeb 09 2025
R-4.4-win-x86_64NOTEFeb 09 2025
R-4.4-mac-x86_64NOTEFeb 09 2025
R-4.4-mac-aarch64NOTEFeb 09 2025
R-4.3-win-x86_64NOTEDec 11 2024
R-4.3-mac-x86_64NOTEDec 11 2024
R-4.3-mac-aarch64NOTEDec 11 2024

Exports:group_cellnbresidualnebulascToNeb

Dependencies:abindaskpassbase64encBHBiobaseBiocGenericsbitopsbslibcachemcaToolscliclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDelayedArraydeldirdigestdoFuturedoRNGdotCall64dplyrdqrngevaluatefansifarverfastDummiesfastmapfitdistrplusFNNfontawesomeforeachfsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleidenbaselifecyclelistenvlmtestmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUImunsellnlmenloptropensslparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppGSLRcppHNSWRcppParallelRcppProgressRcppTOMLRcppZigguratreshape2reticulateRfastrlangrmarkdownrngtoolsROCRrprojrootRSpectraRtsneS4ArraysS4VectorssassscalesscattermoresctransformSeuratSeuratObjectshinySingleCellExperimentsitmosourcetoolsspspamSparseArrayspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytextrustUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzoo

A fast negative binomial mixed model for analyzing multi-subject single-cell data

Liang He

Rendered fromnebula_example.Rmdusingknitr::rmarkdownon Feb 09 2025.

Last update: 2024-02-15
Started: 2020-09-23