distinct
This is the development version of distinct; for the stable release version, see distinct.
distinct: a method for differential analyses via hierarchical permutation tests
Bioconductor version: Development (3.18)
distinct is a statistical method to perform differential testing between two or more groups of distributions; differential testing is performed via hierarchical non-parametric permutation tests on the cumulative distribution functions (cdfs) of each sample. While most methods for differential expression target differences in the mean abundance between conditions, distinct, by comparing full cdfs, identifies, both, differential patterns involving changes in the mean, as well as more subtle variations that do not involve the mean (e.g., unimodal vs. bi-modal distributions with the same mean). distinct is a general and flexible tool: due to its fully non-parametric nature, which makes no assumptions on how the data was generated, it can be applied to a variety of datasets. It is particularly suitable to perform differential state analyses on single cell data (i.e., differential analyses within sub-populations of cells), such as single cell RNA sequencing (scRNA-seq) and high-dimensional flow or mass cytometry (HDCyto) data. To use distinct one needs data from two or more groups of samples (i.e., experimental conditions), with at least 2 samples (i.e., biological replicates) per group.
Author: Simone Tiberi [aut, cre].
Maintainer: Simone Tiberi <simone.tiberi at uzh.ch>
citation("distinct")):
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("distinct")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("distinct")| distinct: a method for differential analyses via hierarchical permutation tests | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DifferentialExpression, FlowCytometry, GeneExpression, GeneTarget, Genetics, MultipleComparison, RNASeq, Sequencing, SingleCell, Software, StatisticalMethod, Transcription, Visualization |
| Version | 1.13.1 |
| In Bioconductor since | BioC 3.11 (R-4.0) (3.5 years) |
| License | GPL (>= 3) |
| Depends | R (>= 4.0) |
| Imports | Rcpp, Rfast, stats, SummarizedExperiment, SingleCellExperiment, methods, Matrix, foreach, parallel, doParallel, doRNG, ggplot2, limma, scater |
| Linking To | Rcpp, RcppArmadillo, Rfast |
| Suggests | knitr, rmarkdown, testthat, UpSetR, BiocStyle |
| System Requirements | C++11 |
| Enhances | |
| URL | https://github.com/SimoneTiberi/distinct |
| Bug Reports | https://github.com/SimoneTiberi/distinct/issues |
See More
| Depends On Me | |
| Imports Me | condiments |
| Suggests Me | spatialHeatmap |
| Links To Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | distinct_1.13.1.tar.gz |
| Windows Binary | distinct_1.13.1.zip |
| macOS Binary (x86_64) | distinct_1.13.1.tgz |
| macOS Binary (arm64) | distinct_1.13.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/distinct |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/distinct |
| Bioc Package Browser | https://code.bioconductor.org/browse/distinct/ |
| Package Short Url | https://bioconductor.org/packages/distinct/ |
| Package Downloads Report | Download Stats |