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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
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Linear model and normality based transformation method (Linnorm)
Bioconductor version: Release (3.4)
Please note that significant updates to Linnorm are available in version 1.99.x +, we strongly suggest using the newest version. 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, the following pipelines are implemented: 1. Cell subpopluation analysis and visualization using PCA clustering, 2. Differential expression analysis or differential peak detection using limma, 3. Highly variable gene discovery and visualization, 4. Gene correlation network analysis and visualization. 5. Hierarchical clustering and plotting. Linnorm can work with raw count, CPM, RPKM, FPKM and TPM. Additionally, Linnorm provides the RnaXSim function for the simulation of RNA-seq raw counts for the evaluation of differential expression analysis methods. RnaXSim can simulate RNA-seq dataset in Gamma, Log Normal, Negative Binomial or Poisson distributions.
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")
| R Script | Linnorm User Manual | |
| Reference Manual | ||
| Text | NEWS | |
| Text | LICENSE |
Details
| biocViews | BatchEffect, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, Genetics, Network, Normalization, PeakDetection, RNASeq, Sequencing, Software, Transcription |
| Version | 1.2.11 |
| In Bioconductor since | BioC 3.3 (R-3.3) (1 year) |
| License | MIT + file LICENSE |
| Depends | R (>= 3.3) |
| Imports | Rcpp (>= 0.12.2), RcppArmadillo, fpc, vegan, mclust, apcluster, ggplot2, ellipse, limma, utils, statmod, MASS, igraph, grDevices, graphics, fastcluster, ggdendro, zoo, stats, amap |
| LinkingTo | Rcpp, RcppArmadillo |
| Suggests | BiocStyle, knitr, rmarkdown, gplots, RColorBrewer |
| 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_1.2.11.tar.gz |
| Windows Binary | Linnorm_1.2.11.zip (32- & 64-bit) |
| Mac OS X 10.9 (Mavericks) | Linnorm_1.2.11.tgz |
| Subversion source | (username/password: readonly) |
| Git source | https://github.com/Bioconductor-mirror/Linnorm/tree/release-3.4 |
| Package Short Url | http://bioconductor.org/packages/Linnorm/ |
| Package Downloads Report | Download Stats |
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