Linnorm
Linear model and normality based normalization and transformation method (Linnorm)
Bioconductor version: 3.24 · Package version: 2.37.0
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
| Maintainer | Shun Hang Yip <shunyip@bu.edu> |
| Author | Shun Hang Yip <shunyip@bu.edu> |
| License | MIT + file LICENSE |
| URL | https://doi.org/10.1093/nar/gkx828 |
| Downloads rank | 686 |
| Source branch | devel |
| biocViews | BatchEffect, 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 package | Linnorm_2.37.0.tar.gz |
| Windows binary (x86_64) | Linnorm_2.37.0.zip |
| macOS binary (arm64) | Linnorm_2.37.0.tgz |
| macOS binary (x86_64) | Linnorm_2.37.0.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