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 (3.18)
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("cytoKernel")):
Installation
To install this package, start R (version "4.3") 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 | ||
| NEWS | Text |
Details
| biocViews | Clustering, DifferentialExpression, FlowCytometry, GeneExpression, ImmunoOncology, OneChannel, Proteomics, SingleCell, Software |
| Version | 1.7.0 |
| In Bioconductor since | BioC 3.14 (R-4.1) (2 years) |
| License | GPL-3 |
| Depends | R (>= 4.1) |
| Imports | Rcpp, SummarizedExperiment, utils, methods, ComplexHeatmap, circlize, ashr, data.table, BiocParallel, dplyr, stats, magrittr, rlang, S4Vectors |
| Linking To | Rcpp |
| Suggests | knitr, rmarkdown, BiocStyle, testthat |
| System Requirements | |
| Enhances | |
| URL | |
| Bug Reports | https://github.com/Ghoshlab/cytoKernel/issues |
See More
| 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_1.7.0.tar.gz |
| Windows Binary | cytoKernel_1.7.0.zip (64-bit only) |
| macOS Binary (x86_64) | cytoKernel_1.7.0.tgz |
| macOS Binary (arm64) | cytoKernel_1.7.0.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 |