• Overview
• Repo Contents
• System Requirements
• Installation Guide
• Instructions for Use
• License
• Issues
• Pseudocode
• Matlab code
• Citation

In modern scientific discovery, it is becoming increasingly critical to uncover whether one property of a dataset is related to another. The MGC (pronounced magic), or Multiscale Graph Correlation, provides a framework for investigation into the relationships between properties of a dataset and the underlying geometries of the relationships, all while requiring sample sizes feasible in real data scenarios.

• R: R package code.
• docs: package documentation.
• man: package manual for help in R session.
• tests: R unit tests written using the testthat package.
• vignettes: R vignettes for R session html help pages.

The MGC package requires only a standard computer with enough RAM to support the operations defined by a user. For minimal performance, this will be a computer with about 2 GB of RAM. For optimal performance, we recommend a computer with the following specs:

RAM: 16+ GB
CPU: 4+ cores, 3.3+ GHz/core

The runtimes below are generated using a computer with the recommended specs (16 GB RAM, 4 [email protected] GHz) and internet of speed 25 Mbps.

This package is supported for Linux operating systems. The package has been tested on the following systems:

Linux: Ubuntu 16.04
Mac OSX:
Windows:

Before setting up the MGC package, users should have R version 3.4.0 or higher, and several packages set up from CRAN.

the latest version of R can be installed by adding the latest repository to apt:

sudo echo "deb http://cran.rstudio.com/bin/linux/ubuntu xenial/" | sudo tee -a /etc/apt/sources.list
gpg --keyserver keyserver.ubuntu.com --recv-key E084DAB9
gpg -a --export E084DAB9 | sudo apt-key add -
sudo apt-get update
sudo apt-get install r-base r-base-dev

which should install in about 20 seconds.

Users should install the following packages prior to installing mgc, from an R terminal:

install.packages(c('ggplot2', 'reshape2', 'Rmisc', 'devtools', 'testthat', 'knitr', 'rmarkdown', 'latex2exp', 'MASS'))

which will install in about 80 seconds on a recommended machine.

The mgc package functions with all packages in their latest versions as they appear on CRAN on October 15, 2017. Users can check CRAN snapshot for details. The versions of software are, specifically:

ggplot2: 2.2.1
reshape2: 1.4.2
Rmisc: 1.5
devtools: 1.13.3
testthat: 0.2.0
knitr: 1.17
rmarkdown: 1.6
latex2exp: 0.4.0
MASS: 7.3

If you are having an issue that you believe to be tied to software versioning issues, please drop us an Issue.

From an R session, type:

require(devtools)
install_github('neurodata/mgc', build_vignettes=TRUE)  # install mgc with the vignettes
require(mgc)  # source the package now that it is set up
vignette("MGC", package="mgc")  # view one of the basic vignettes

The package should take approximately 20 seconds to install with vignettes on a recommended computer.

Please see the vignettes for help using the package:

vignette("MGC", package="mgc")
vignette("Discriminability", package="mgc")
vignette("simulations", package="mgc")

Pseudocode for the methods employed in the mgc package can be found on the arXiv - MGC in Appendix C (starting on page 30).

For citing code or the paper, please use the citations found in citation.bib.

All the code to reproduce any figures from https://arxiv.org/abs/1609.05148 is available here https://github.com/neurodata/mgc-paper