cytoKernel

DOI: 10.18129/B9.bioc.cytoKernel    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see cytoKernel.

Differential expression using kernel-based score test

Bioconductor version: 3.15

cytoKernel implements a kernel-based score test to identify differentially expressed features in high-dimensional biological experiments. This approach can be applied across many different high-dimensional biological data including gene expression data and dimensionally reduced cytometry-based marker expression data. In this R package, we implement functions that compute the feature-wise p values and their corresponding adjusted p values. Additionally, it also computes the feature-wise shrunk effect sizes and their corresponding shrunken effect size. Further, it calculates the percent of differentially expressed features and plots user-friendly heatmap of the top differentially expressed features on the rows and samples on the columns.

Author: Tusharkanti Ghosh [aut, cre], Victor Lui [aut], Pratyaydipta Rudra [aut], Souvik Seal [aut], Thao Vu [aut], Elena Hsieh [aut], Debashis Ghosh [aut, cph]

Maintainer: Tusharkanti Ghosh <tusharkantighosh30 at gmail.com>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("cytoKernel")

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("cytoKernel")

 

HTML	R Script	The CytoK user's guide
PDF		Reference Manual
Text		NEWS

Details

biocViews	Clustering, DifferentialExpression, FlowCytometry, GeneExpression, ImmunoOncology, OneChannel, Proteomics, SingleCell, Software
Version	1.2.0
In Bioconductor since	BioC 3.14 (R-4.1) (1 year)
License	GPL-3
Depends	R (>= 4.1)
Imports	Rcpp, SummarizedExperiment, utils, methods, ComplexHeatmap, circlize, ashr, data.table, BiocParallel, dplyr, stats, magrittr, rlang, S4Vectors
LinkingTo	Rcpp
Suggests	knitr, rmarkdown, BiocStyle, testthat
SystemRequirements
Enhances
URL
BugReports	https://github.com/Ghoshlab/cytoKernel/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	cytoKernel_1.2.0.tar.gz
Windows Binary	cytoKernel_1.2.0.zip
macOS Binary (x86_64)	cytoKernel_1.2.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/cytoKernel
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/cytoKernel
Package Short Url	https://bioconductor.org/packages/cytoKernel/
Package Downloads Report	Download Stats