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marr

This is the development version of marr; for the stable release version, see marr.

Maximum rank reproducibility


Bioconductor version: Development (3.19)

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 (from within R, enter citation("marr")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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 PDF
NEWS Text

Details

biocViews ChIPSeq, MassSpectrometry, Metabolomics, QualityControl, RNASeq, Software
Version 1.13.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 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_1.13.0.tar.gz
Windows Binary marr_1.13.0.zip (64-bit only)
macOS Binary (x86_64) marr_1.13.0.tgz
macOS Binary (arm64) marr_1.13.0.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