Contents

1 Installation

The package can be installed from bioconductor

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("scDDboost")

Issue can be reported at “https://github.com/wiscstatman/scDDboost/issues”

2 Introduction

scDDboost scores evidence of a gene being differentially distributed(DD) across two conditions for single cell RNA-seq data. Higher resolution brings several chanllenges for analyzing the data, specifically, the distribution of gene expression tends to have high prevalence of zero and multi-modes. To account for those characteristics and utilizing some biological intuition, we view the expression values sampled from a pool of cells mixed by distinct cellular subtypes blind to condition label. Consequently, the distributional change can be fully determined by the the change of subtype proportions. One tricky part is that not any change of proportions will lead to a distributional change. Given that some genes could be equivalent expressed across several subtypes, even the individual subytpe proportion may differ between conditions but as long as the aggregated proportions over those subtypes remain the same between conditions, it will not introduce different distribution. For example

Proportions of subtypes 1 and 2 changed between the 2 conditions. The gene is not DD if subtype 1 and 2 have the same expression level

For subtype 1 and 2 have different expression level, there is different distribution