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

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Documentation for package ‘scDDboost’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

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