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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 (3.5)
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")
| R Script | Linnorm User Manual | |
| 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) (1.5 years) |
| 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.
| Source Package | 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 |
| Source Repository | git clone https://git.bioconductor.org/packages/Linnorm |
| Package Short Url | http://bioconductor.org/packages/Linnorm/ |
| Package Downloads Report | Download Stats |
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