README.md

PhysioSpace Methods

PhysioSpace is a robust statistical method for relating high dimensional omics data, published in Lenz et. al.^[Lenz, Michael, et al. "PhysioSpace: relating gene expression experiments from heterogeneous sources using shared physiological processes." PLoS One 8.10 (2013): e77627]. It is designed to take advantage of the vast availability of public omics data, which in combination with statistical approaches make a potent tool capable of analyzing heterogenious biological data sets.

PhysioSpaceMethods is a R package which provides an implementation of PhysioSpace method alongside other handy functions for making PhysioSpace an easy accessible tool for R users.

Table of Contents

Installation Instructions
Usage Instructions

Installation Instructions

Installing via Devtools (Recommended method):

Easiest way to install PhysioSpaceMethods is via Devtools. After installing Devtools from cran, you can install PhysioSpaceMethods by:

devtools::install_github(repo = "JRC-COMBINE/PhysioSpaceMethods", build_vignettes = TRUE)

Alternative installation methods (Manual download):

In case you encountered any problem while installing PhysioSpaceMethods, you can download the repository first and install the package from downloaded local files. In your terminal, first clone the repository in your desired repository:

cd [Your desired directory]
git clone https://github.com/JRC-COMBINE/PhysioSpaceMethods.git

Then install the downloaded package using Devtools:

R -e "devtools::install_local('./PhysioSpaceMethods/', build_vignettes = TRUE)"

Usage Instructions

PhysioSpaceMethods can map user samples inside a physiological space, calculated prior from a compendium of known samples. Explanation of how to use this package is provided in a vignette, which can be access by:

browseVignettes(package = "PhysioSpaceMethods")

Test Environments

The package was tested with R 3.4 on Windows 10, Mac OS X and Linux (CentOS 7.4).