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Bioconductor - Linnorm (development version)

Linnorm

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

Linear model and normality based normalization and transformation method (Linnorm)

Bioconductor version: Development (3.22)

Linnorm is an algorithm for normalizing and transforming RNA-seq, single cell RNA-seq, ChIP-seq count data or any large scale count data. It has been independently reviewed by Tian et al. on Nature Methods (https://doi.org/10.1038/s41592-019-0425-8). Linnorm can work with raw count, CPM, RPKM, FPKM and TPM.

Author: Shun Hang Yip <shunyip at bu.edu>

Maintainer: Shun Hang Yip <shunyip at bu.edu>

Citation (from within R, enter citation("Linnorm")): Installation

To install this package, start R (version "4.5") and enter:


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

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

BiocManager::install("Linnorm")

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("Linnorm")
Details biocViews BatchEffect, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, Genetics, ImmunoOncology, Network, Normalization, PeakDetection, RNASeq, Sequencing, SingleCell, Software, Transcription Version 2.33.0 In Bioconductor since BioC 3.3 (R-3.3) (9 years) License MIT + file LICENSE Depends R (>= 4.1.0) Imports Rcpp (>= 0.12.2), RcppArmadillo (>= 0.8.100.1.0), fpc, vegan, mclust, apcluster, ggplot2, ellipse, limma, utils, statmod, MASS, igraph, grDevices, graphics, fastcluster, ggdendro, zoo, stats, amap, Rtsne, gmodels System Requirements URL https://doi.org/10.1093/nar/gkx828 See More Package Archives

Follow Installation instructions to use this package in your R session.

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