PCAtools

DOI: 10.18129/B9.bioc.PCAtools    

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

PCAtools: everything Principal Components Analysis

Bioconductor version: Development (3.9)

Principal Components Analysis (PCA) is a very powerful technique that has wide applicability in data science, bioinformatics, and further afield. It was initially developed to analyse large volumes of data in order to tease out the differences/relationships between the logical entities being analysed. It extracts the fundamental structure of the data without the need to build any model to represent it. This 'summary' of the data is arrived at through a process of reduction that can transform the large number of variables into a lesser number that are uncorrelated, i.e., the principal components, whilst at the same time being capable of easy interpretation on the original data.

Author: Kevin Blighe, Myles Lewis

Maintainer: Kevin Blighe <kevin at clinicalbioinformatics.co.uk>, Myles Lewis <myles.lewis at qmul.ac.uk>

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

Installation

To install this package, start R (version "3.6") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("PCAtools", version = "3.9")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("PCAtools")

 

HTML R Script PCAtools: everything Principal Components Analysis
PDF   Reference Manual
Text   NEWS

Details

biocViews GeneExpression, RNASeq, Software, Transcription
Version 0.99.13
In Bioconductor since BioC 3.9 (R-3.6)
License GPL-3
Depends stats, ggplot2, ggrepel, reshape2, lattice, grDevices, cowplot
Imports
LinkingTo
Suggests RUnit, BiocGenerics, knitr, Biobase, GEOquery, biomaRt, ggplotify
SystemRequirements
Enhances
URL https://github.com/kevinblighe/PCAtools
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package PCAtools_0.99.13.tar.gz
Windows Binary PCAtools_0.99.13.zip
Mac OS X 10.11 (El Capitan) PCAtools_0.99.13.tgz
Source Repository git clone https://git.bioconductor.org/packages/PCAtools
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/PCAtools
Package Short Url http://bioconductor.org/packages/PCAtools/
Package Downloads Report Download Stats

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