Package: scDDboost 1.9.2
scDDboost: A compositional model to assess expression changes from single-cell rna-seq data
scDDboost is an R package to analyze changes in the distribution of single-cell expression data between two experimental conditions. Compared to other methods that assess differential expression, scDDboost benefits uniquely from information conveyed by the clustering of cells into cellular subtypes. Through a novel empirical Bayesian formulation it calculates gene-specific posterior probabilities that the marginal expression distribution is the same (or different) between the two conditions. The implementation in scDDboost treats gene-level expression data within each condition as a mixture of negative binomial distributions.
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scDDboost.pdf |scDDboost.html✨
scDDboost/json (API)
# Install 'scDDboost' in R: |
install.packages('scDDboost', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/wiscstatman/scddboost/issues
- sim_dat - ScDDboost
On BioConductor:scDDboost-1.9.1(bioc 3.21)scDDboost-1.8.0(bioc 3.20)
singlecellsoftwareclusteringsequencinggeneexpressiondifferentialexpressionbayesiancpp
Last updated 23 days agofrom:c913cbeacb. Checks:1 OK, 8 NOTE, 2 WARNING. Indexed: yes.
Target | Result | Latest binary |
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Doc / Vignettes | OK | Jan 29 2025 |
R-4.5-win-x86_64 | NOTE | Jan 29 2025 |
R-4.5-mac-x86_64 | WARNING | Jan 29 2025 |
R-4.5-mac-aarch64 | WARNING | Jan 29 2025 |
R-4.5-linux-x86_64 | NOTE | Jan 29 2025 |
R-4.4-win-x86_64 | NOTE | Jan 29 2025 |
R-4.4-mac-x86_64 | NOTE | Jan 29 2025 |
R-4.4-mac-aarch64 | NOTE | Jan 29 2025 |
R-4.3-win-x86_64 | NOTE | Jan 29 2025 |
R-4.3-mac-x86_64 | NOTE | Jan 29 2025 |
R-4.3-mac-aarch64 | NOTE | Jan 29 2025 |
Exports:calDdetKextractInfogetDDgetSizeofDDpatpdd
Dependencies:abindaskpassBHBiobaseBiocGenericsBiocParallelbitopsblockmodelingbriocallrcaToolscliclustercodetoolscolorspacecpp11crayoncurlDelayedArraydescdiffobjdigestEBSeqevaluatefansifarverformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegplotsgtablegtoolshttrIRangesisobandjsonliteKernSmoothlabelinglambda.rlatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmclustmgcvmimemunsellnlmeopensslOscopepillarpkgbuildpkgconfigpkgloadpraiseprocessxpsR6RColorBrewerRcppRcppEigenrlangrprojrootS4ArraysS4VectorsscalesSingleCellExperimentsnowSparseArraySummarizedExperimentsystestthattibbleUCSC.utilsutf8vctrsviridisLitewaldowithrXVector