Package: scDDboost 1.7.0

Xiuyu Ma

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.

Authors:Xiuyu Ma [cre, aut], Michael A. Newton [ctb]

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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

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

sim_dat - ScDDboost

On BioConductor:scDDboost-1.7.0(bioc 3.20)scDDboost-1.6.0(bioc 3.19)

bioconductor-package

7 exports 0.49 score 91 dependencies

Last updated 2 months agofrom:68a6e0dfce

Exports:calD detK extractInfo getDD getSizeofDD pat pdd

Dependencies:abind askpass BH Biobase BiocGenerics BiocParallel bitops blockmodeling brio callr caTools cli cluster codetools colorspace cpp11 crayon curl DelayedArray desc diffobj digest EBSeq evaluate fansi farver formatR fs futile.logger futile.options GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 glue gplots gtable gtools httr IRanges isoband jsonlite KernSmooth labeling lambda.r lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats mclust mgcv mime munsell nlme openssl Oscope pillar pkgbuild pkgconfig pkgload praise processx ps R6 RColorBrewer Rcpp RcppEigen rematch2 rlang rprojroot S4Arrays S4Vectors scales SingleCellExperiment snow SparseArray SummarizedExperiment sys testthat tibble UCSC.utils utf8 vctrs viridisLite waldo withr XVector zlibbioc

scDDboost

Xiuyu Ma

Rendered fromscDDboost.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2022-05-29
Started: 2021-09-08

Help page	Topics
A compositional model to assess expression changes from single-cell rna-seq data	scDDboost-package scDDboost
calculate distance matrix	calD
function to get intra and inter distance for clusters	clusHelper
determine the number of clusters	detK
accelerated empirical bayesian	EBS
extract count matrix from SingleCellExperiment object	extractInfo
gene_level cluster	gCl
generate random clusterings	genRClus
index of DD genes under FDR control	getDD
number of DD genes under FDR control	getSizeofDD
function to get counts of cluster sizes at two conditions	getZ1Z2
generate reference matrix	gRef
check refinement relation between two clusters	isRef
likelihood function for hyperparameters estimation	LL
log likelihood of z1,z2 given t1,t2	lpt1t2
log likelihood of aggregated multinomial counts z given aggregated proportions t	lpzgt
posterior of proportion change given mixture double dirichlet prior	mdd
generating partition patterns	pat
calculate posterior probabilities of a gene to be differential distributed	pdd
function to aggregate intermediate results and get prob of DD	pddAggregate
MLE for random weighting parameter	rwMle
scDDboost	sim_dat

Package: scDDboost 1.7.0

scDDboost: A compositional model to assess expression changes from single-cell rna-seq data

scDDboost

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