marr

DOI: 10.18129/B9.bioc.marr    

This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see marr.

Maximum rank reproducibility

Bioconductor version: 3.13

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>

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("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")

 

HTML	R Script	The marr user's guide
PDF		Reference Manual
Text		NEWS

Details

biocViews	ChIPSeq, MassSpectrometry, Metabolomics, QualityControl, RNASeq, Software
Version	1.2.0
In Bioconductor since	BioC 3.12 (R-4.0) (1 year)
License	GPL (>= 3)
Depends	R (>= 4.0)
Imports	Rcpp, SummarizedExperiment, utils, methods, ggplot2, dplyr, magrittr, rlang, S4Vectors
LinkingTo	Rcpp
Suggests	knitr, rmarkdown, BiocStyle, testthat, covr
SystemRequirements
Enhances
URL
BugReports	https://github.com/Ghoshlab/marr/issues
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	marr_1.2.0.tar.gz
Windows Binary	marr_1.2.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	marr_1.2.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/marr
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/marr
Package Short Url	https://bioconductor.org/packages/marr/
Package Downloads Report	Download Stats