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POWSC

This is the development version of POWSC; for the stable release version, see POWSC.

Simulation, power evaluation, and sample size recommendation for single cell RNA-seq


Bioconductor version: Development (3.19)

Determining the sample size for adequate power to detect statistical significance is a crucial step at the design stage for high-throughput experiments. Even though a number of methods and tools are available for sample size calculation for microarray and RNA-seq in the context of differential expression (DE), this topic in the field of single-cell RNA sequencing is understudied. Moreover, the unique data characteristics present in scRNA-seq such as sparsity and heterogeneity increase the challenge. We propose POWSC, a simulation-based method, to provide power evaluation and sample size recommendation for single-cell RNA sequencing DE analysis. POWSC consists of a data simulator that creates realistic expression data, and a power assessor that provides a comprehensive evaluation and visualization of the power and sample size relationship.

Author: Kenong Su [aut, cre], Hao Wu [aut]

Maintainer: Kenong Su <kenong.su at emory.edu>

Citation (from within R, enter citation("POWSC")):

Installation

To install this package, start R (version "4.4") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("POWSC")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("POWSC")
The POWSC User's Guide HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, ImmunoOncology, SingleCell, Software
Version 1.11.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-2
Depends R (>= 4.1), Biobase, SingleCellExperiment, MAST
Imports pheatmap, ggplot2, RColorBrewer, grDevices, SummarizedExperiment, limma
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Suggests rmarkdown, knitr, testthat (>= 3.0.0), BiocStyle
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package POWSC_1.11.0.tar.gz
Windows Binary POWSC_1.11.0.zip
macOS Binary (x86_64) POWSC_1.11.0.tgz
macOS Binary (arm64) POWSC_1.11.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/POWSC
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/POWSC
Bioc Package Browser https://code.bioconductor.org/browse/POWSC/
Package Short Url https://bioconductor.org/packages/POWSC/
Package Downloads Report Download Stats