Power Analysis
Power Analysis for Differential Expression in scRNA-seq data


R build status
License: MIT + file LICENSE

Authors: Salman Fawad, Alan Murphy, Yunning Yuan, Hiranyamaya (Hiru) Dash, Nathan Skene
Updated: May-21-2025

Introduction

The poweranalysis R package is designed to run robust power analysis for differential gene expression in scRNA-seq studies and provides tools to estimate the optimal number of samples and cells needed to achieve reliable power levels.

Wraps work from this repository into an R package.

To install:

devtools::install_github("neurogenomics/Power_Analysis")

Load:

Contact

Neurogenomics Lab

UK Dementia Research Institute
Department of Brain Sciences
Faculty of Medicine
Imperial College London
GitHub

Session Info 

utils::sessionInfo()
## R version 4.5.0 (2025-04-11)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.2 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] rmarkdown_2.29
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.6        jsonlite_2.0.0      dplyr_1.1.4        
##  [4] compiler_4.5.0      BiocManager_1.30.25 renv_1.1.4         
##  [7] tidyselect_1.2.1    rvcheck_0.2.1       scales_1.4.0       
## [10] yaml_2.3.10         fastmap_1.2.0       here_1.0.1         
## [13] ggplot2_3.5.2       R6_2.6.1            generics_0.1.4     
## [16] knitr_1.50          yulab.utils_0.2.0   tibble_3.2.1       
## [19] desc_1.4.3          dlstats_0.1.7       rprojroot_2.0.4    
## [22] pillar_1.10.2       RColorBrewer_1.1-3  rlang_1.1.6        
## [25] badger_0.2.4        xfun_0.52           fs_1.6.6           
## [28] cli_3.6.5           magrittr_2.0.3      rworkflows_1.0.6   
## [31] digest_0.6.37       grid_4.5.0          lifecycle_1.0.4    
## [34] vctrs_0.6.5         evaluate_1.0.3      glue_1.8.0         
## [37] data.table_1.17.2   farver_2.1.2        tools_4.5.0        
## [40] pkgconfig_2.0.3     htmltools_0.5.8.1