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

Bioconductor version: Release (3.19)

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 ( Linnorm can work with raw count, CPM, RPKM, FPKM and TPM.

Author: Shun Hang Yip <shunyip at>

Maintainer: Shun Hang Yip <shunyip at>

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


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

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Linnorm User Manual PDF R Script
Reference Manual PDF


biocViews BatchEffect, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, Genetics, ImmunoOncology, Network, Normalization, PeakDetection, RNASeq, Sequencing, SingleCell, Software, Transcription
Version 2.28.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License MIT + file LICENSE
Depends R (>= 4.1.0)
Imports Rcpp (>= 0.12.2), RcppArmadillo (>=, fpc, vegan, mclust, apcluster, ggplot2, ellipse, limma, utils, statmod, MASS, igraph, grDevices, graphics, fastcluster, ggdendro, zoo, stats, amap, Rtsne, gmodels
System Requirements
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Suggests BiocStyle, knitr, rmarkdown, markdown, gplots, RColorBrewer, moments, testthat, matrixStats
Linking To Rcpp, RcppArmadillo
Depends On Me
Imports Me mnem
Suggests Me SCdeconR
Links To Me
Build Report Build Report

Package Archives

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

Source Package Linnorm_2.28.0.tar.gz
Windows Binary
macOS Binary (x86_64) Linnorm_2.28.0.tgz
macOS Binary (arm64) Linnorm_2.28.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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