cytoKernel

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see cytoKernel.

Differential expression using kernel-based score test


Bioconductor version: 3.17

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>

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

Installation

To install this package, start R (version "4.3") 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")
The CytoK user's guide HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Clustering, DifferentialExpression, FlowCytometry, GeneExpression, ImmunoOncology, OneChannel, Proteomics, SingleCell, Software
Version 1.6.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License GPL-3
Depends R (>= 4.1)
Imports Rcpp, SummarizedExperiment, utils, methods, ComplexHeatmap, circlize, ashr, data.table, BiocParallel, dplyr, stats, magrittr, rlang, S4Vectors
System Requirements
URL
Bug Reports https://github.com/Ghoshlab/cytoKernel/issues
See More
Suggests knitr, rmarkdown, BiocStyle, testthat
Linking To Rcpp
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package cytoKernel_1.6.0.tar.gz
Windows Binary cytoKernel_1.6.0.zip
macOS Binary (x86_64) cytoKernel_1.6.0.tgz
macOS Binary (arm64) cytoKernel_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/cytoKernel
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/cytoKernel
Bioc Package Browser https://code.bioconductor.org/browse/cytoKernel/
Package Short Url https://bioconductor.org/packages/cytoKernel/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.17 Source Archive