This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see distinct.
Bioconductor version: 3.16
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 (from within R,
enter citation("distinct")
):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("distinct")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("distinct")
HTML | R Script | distinct: a method for differential analyses via hierarchical permutation tests |
Reference Manual | ||
Text | NEWS |
biocViews | DifferentialExpression, FlowCytometry, GeneExpression, GeneTarget, Genetics, MultipleComparison, RNASeq, Sequencing, SingleCell, Software, StatisticalMethod, Transcription, Visualization |
Version | 1.10.2 |
In Bioconductor since | BioC 3.11 (R-4.0) (3 years) |
License | GPL (>= 3) |
Depends | R (>= 4.0) |
Imports | Rcpp, Rfast, stats, SummarizedExperiment, SingleCellExperiment, methods, Matrix, foreach, parallel, doParallel, doRNG, ggplot2, limma, scater |
LinkingTo | Rcpp, RcppArmadillo, Rfast |
Suggests | knitr, rmarkdown, testthat, UpSetR |
SystemRequirements | C++11 |
Enhances | |
URL | https://github.com/SimoneTiberi/distinct |
BugReports | https://github.com/SimoneTiberi/distinct/issues |
Depends On Me | |
Imports Me | condiments |
Suggests Me | spatialHeatmap |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | distinct_1.10.2.tar.gz |
Windows Binary | distinct_1.10.2.zip (64-bit only) |
macOS Binary (x86_64) | distinct_1.10.2.tgz |
macOS Binary (arm64) | distinct_1.10.2.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/distinct |
Source Repository (Developer Access) | git clone [email protected]:packages/distinct |
Bioc Package Browser | https://code.bioconductor.org/browse/distinct/ |
Package Short Url | https://bioconductor.org/packages/distinct/ |
Package Downloads Report | Download Stats |
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