NormalyzerDE

Evaluation of normalization methods and calculation of differential expression analysis statistics

Bioconductor version: 3.23 · Package version: 1.30.0

NormalyzerDE provides screening of normalization methods for LC-MS based expression data. It calculates a range of normalized matrices using both existing approaches and a novel time-segmented approach, calculates performance measures and generates an evaluation report. Furthermore, it provides an easy utility for Limma- or ANOVA- based differential expression analysis.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("NormalyzerDE")

Details

Maintainer	Jakob Willforss <jakob.willforss@hotmail.com>
Author	Jakob Willforss
License	Artistic-2.0
URL	https://computationalproteomics.github.io/NormalyzerDE/, https://github.com/ComputationalProteomics/NormalyzerDE
Downloads rank	476
Source branch	RELEASE_3_23
biocViews	Bayesian, DifferentialExpression, Metabolomics, MultipleComparison, Normalization, Proteomics, Software, Visualization

Documentation

Evaluation and statistics of expression data using NormalyzerDE

Download

Source package

Dependencies

Depends: R (>= 4.1.0)

Imports: vsn, preprocessCore, limma, MASS, ape, car, ggplot2, methods, utils, stats, SummarizedExperiment, matrixStats, ggforce

Suggests: knitr, testthat, rmarkdown, roxygen2, hexbin, BiocStyle

Reverse dependencies

Imports Me (1): PRONE