To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("Linnorm")

In most cases, you don't need to download the package archive at all.

Linnorm

 

Linear model and normality based transformation method (Linnorm)

Bioconductor version: Release (3.5)

Linnorm is an R package for the analysis of RNA-seq, scRNA-seq, ChIP-seq count data or any large scale count data. It transforms such datasets for parametric tests. In addition to the transformtion function (Linnorm), the following pipelines are implemented: 1. Library size/Batch effect normalization (Linnorm.Norm), 2. Cell subpopluation analysis and visualization using t-SNE or PCA K-means clustering or Hierarchical clustering (Linnorm.tSNE, Linnorm.PCA, Linnorm.HClust), 3. Differential expression analysis or differential peak detection using limma (Linnorm.limma), 4. Highly variable gene discovery and visualization (Linnorm.HVar), 5. Gene correlation network analysis and visualization (Linnorm.Cor), 6. Stable gene selection for scRNA-seq data; for users without or do not want to rely on spike-in genes (Linnorm.SGenes). 7. Data imputation. (under development) (Linnorm.DataImput). Linnorm can work with raw count, CPM, RPKM, FPKM and TPM. Additionally, the RnaXSim function is included for simulating RNA-seq data for the evaluation of DEG analysis methods.

Author: Shun Hang Yip <shunyip at bu.edu>, Panwen Wang <pwwang at pwwang.com>, Jean-Pierre Kocher <Kocher.JeanPierre at mayo.edu>, Pak Chung Sham <pcsham at hku.hk>, Junwen Wang <junwen at uw.edu>

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

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("Linnorm")

Documentation

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

browseVignettes("Linnorm")

 

PDF R Script Linnorm User Manual
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews BatchEffect, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, Genetics, Network, Normalization, PeakDetection, RNASeq, Sequencing, SingleCell, Software, Transcription
Version 2.0.8
In Bioconductor since BioC 3.3 (R-3.3) (1 year)
License MIT + file LICENSE
Depends R (>= 3.4)
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
LinkingTo Rcpp, RcppArmadillo
Suggests BiocStyle, knitr, rmarkdown, gplots, RColorBrewer, moments, testthat
SystemRequirements
Enhances
URL http://www.jjwanglab.org/Linnorm/
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source Linnorm_2.0.8.tar.gz
Windows Binary Linnorm_2.0.8.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) Linnorm_2.0.8.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/Linnorm/tree/release-3.5
Package Short Url http://bioconductor.org/packages/Linnorm/
Package Downloads Report Download Stats

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