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marr

Maximum rank reproducibility

Bioconductor version: 3.24 · Package version: 1.23.0

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.

Installation

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

BiocManager::install("marr")

Details

MaintainerTusharkanti Ghosh <tusharkantighosh30@gmail.com>
AuthorTusharkanti Ghosh [aut, cre], Max McGrath [aut], Daisy Philtron [aut], Katerina Kechris [aut], Debashis Ghosh [aut, cph]
LicenseGPL (>= 3)
Bug Reportshttps://github.com/Ghoshlab/marr/issues
Downloads rank429
Source branchdevel
biocViewsChIPSeq, MassSpectrometry, Metabolomics, QualityControl, RNASeq, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagemarr_1.23.0.tar.gz
Windows binary (x86_64)marr_1.23.0.zip
macOS binary (arm64)marr_1.23.0.tgz
macOS binary (x86_64)marr_1.23.0.tgz
Dependencies

Depends: R (>= 4.0)

Imports: Rcpp, SummarizedExperiment, utils, methods, ggplot2, dplyr, magrittr, rlang, S4Vectors

LinkingTo: Rcpp

Suggests: knitr, rmarkdown, BiocStyle, testthat, covr