marr
Maximum rank reproducibility
Bioconductor version: Release (3.20)
marr (Maximum Rank Reproducibility) is a nonparametric approach that detects reproducible signals using a maximal rank statistic for high-dimensional biological data. In this R package, we implement functions that measures the reproducibility of features per sample pair and sample pairs per feature in high-dimensional biological replicate experiments. The user-friendly plot functions in this package also plot histograms of the reproducibility of features per sample pair and sample pairs per feature. Furthermore, our approach also allows the users to select optimal filtering threshold values for the identification of reproducible features and sample pairs based on output visualization checks (histograms). This package also provides the subset of data filtered by reproducible features and/or sample pairs.
Author: Tusharkanti Ghosh [aut, cre], Max McGrath [aut], Daisy Philtron [aut], Katerina Kechris [aut], Debashis Ghosh [aut, cph]
Maintainer: Tusharkanti Ghosh <tusharkantighosh30 at gmail.com>
citation("marr")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("marr")
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("marr")
The marr user's guide | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | ChIPSeq, MassSpectrometry, Metabolomics, QualityControl, RNASeq, Software |
Version | 1.16.0 |
In Bioconductor since | BioC 3.12 (R-4.0) (4 years) |
License | GPL (>= 3) |
Depends | R (>= 4.0) |
Imports | Rcpp, SummarizedExperiment, utils, methods, ggplot2, dplyr, magrittr, rlang, S4Vectors |
System Requirements | |
URL | |
Bug Reports | https://github.com/Ghoshlab/marr/issues |
See More
Suggests | knitr, rmarkdown, BiocStyle, testthat, covr |
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 | marr_1.16.0.tar.gz |
Windows Binary (x86_64) | marr_1.16.0.zip |
macOS Binary (x86_64) | marr_1.16.0.tgz |
macOS Binary (arm64) | marr_1.15.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/marr |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/marr |
Bioc Package Browser | https://code.bioconductor.org/browse/marr/ |
Package Short Url | https://bioconductor.org/packages/marr/ |
Package Downloads Report | Download Stats |