marr

DOI: 10.18129/B9.bioc.marr    

Maximum rank reproducibility

Bioconductor version: Release (3.12)

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).

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 "4.0") 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 1.0.0
In Bioconductor since BioC 3.12 (R-4.0) (< 6 months)
License GPL (>= 3)
Depends R (>= 4.0)
Imports Rcpp, SummarizedExperiment, utils, methods, ggplot2
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_1.0.0.tar.gz
Windows Binary marr_1.0.0.zip
macOS 10.13 (High Sierra) marr_1.0.0.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

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