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cytoKernel

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

Differential expression using kernel-based score test


Bioconductor version: Development (3.19)

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 "4.4") and enter:


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

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

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 1.9.0
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
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Package Archives

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

Source Package cytoKernel_1.9.0.tar.gz
Windows Binary cytoKernel_1.9.0.zip
macOS Binary (x86_64) cytoKernel_1.9.0.tgz
macOS Binary (arm64) cytoKernel_1.9.0.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