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Linnorm

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

Bioconductor version: 3.23 · Package version: 2.36.0

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.

Installation

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

BiocManager::install("Linnorm")

Details

MaintainerShun Hang Yip <shunyip@bu.edu>
AuthorShun Hang Yip <shunyip@bu.edu>
LicenseMIT + file LICENSE
URLhttps://doi.org/10.1093/nar/gkx828
Downloads rank686
Source branchRELEASE_3_23
biocViewsBatchEffect, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, Genetics, ImmunoOncology, Network, Normalization, PeakDetection, RNASeq, Sequencing, SingleCell, Software, Transcription

Documentation

Download

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

Source packageLinnorm_2.36.0.tar.gz
Windows binary (x86_64)Linnorm_2.36.0.zip
macOS binary (arm64)Linnorm_2.36.0.tgz
macOS binary (x86_64)Linnorm_2.36.0.tgz
Dependencies

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

LinkingTo: Rcpp, RcppArmadillo

Suggests: BiocStyle, knitr, rmarkdown, markdown, gplots, RColorBrewer, moments, testthat, matrixStats

Reverse dependencies

Imports Me (1): mnem