DOI: 10.18129/B9.bioc.Linnorm    

This is the development version of Linnorm; to use it, please install the devel version of Bioconductor.

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

Bioconductor version: Development (3.10)

Linnorm normalizes and performs variance-stabilizing transformation on RNA-seq, single cell RNA-seq, ChIP-seq count data or any large scale count data. In addition to the main normalization/transformtion function (Linnorm), the following functions 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.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). Linnorm can work with raw count, CPM, RPKM, FPKM and TPM.

Author: Shun Hang Yip <shunyip at>, Panwen Wang <pwwang at>, Jean-Pierre Kocher <Kocher.JeanPierre at>, Pak Chung Sham <pcsham at>, Junwen Wang <junwen at>

Maintainer: Ken Shun Hang Yip <shunyip at>

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


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biocViews BatchEffect, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, Genetics, ImmunoOncology, Network, Normalization, PeakDetection, RNASeq, Sequencing, SingleCell, Software, Transcription
Version 2.9.4
In Bioconductor since BioC 3.3 (R-3.3) (3.5 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
Depends On Me
Imports Me mnem
Suggests Me
Links To Me
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