PhiMRF

R package for Poisson Hierarchical Markov Random Field model for analysis of spatial dependency on count data.

Hierarchical Markov Random Field model captures spatial dependency in gene expression, demonstrating regulation via the 3D genome

Naihui Zhou, Iddo Friedberg, Mark S. Kaiser

bioRxiv 2019.12.16.878371;

doi: https://doi.org/10.1101/2019.12.16.878371

Package Features

Spatial dependency for count data.

Spatial neighborhoods are represented by networks, and thus not limited to regular lattices.

Fast and parallel computation.

The MCMC process is written in C and takes advantage of BLAS and LAPACK routines. OpenMP enables parallel computation.

Large matrices friendly.

The package has special functions that handles large matrices that would otherwise crash your R.

To apply PhiMRF on gene expression and HiC data, see bioMRF.

Model Description

See Vignettes

Installation

Update: Docker image now available through Github packages!

The Docker image has all prerequisites and the PhiMRF R package already installed and ready to use.

Prerequisites

1. Lapacke

Lapacke is a C interface to LAPACK routines. To install on linux if you don't already have lapack and openblas:

sudo apt install liblapack3 
sudo apt install liblapack-dev 
sudo apt install libopenblas-base 
sudo apt install libopenblas-dev 
sudo apt install liblapacke-dev 
sudo apt install liblapack-dev

See here for instructions for Windows.

2. Rmath Standalone library

Rmath enables the use of common R functions such as rnorm() in C.

Here is a brief outline:

1. Find your R home directory by running R.home() within R.

2. Go to your R home directory ($R_HOME) and see if the the directory $R_HOME/src/nmath/standalone/ exists

• If yes, run make in that directory.

• If not, install R from source, and then go to the steps above.

3. Link the Rmath library to the default path

ln -s $R_HOME/src/nmath/standalone/libRmath.so  /usr/lib/libRmath.so

Detailed installation instructions for Rmath can be found here for Linux, MacOS and Windows.

3. Check if you have the required libraries

In a command-line console, type:

ldconfig -p | grep liblapacke
ldconfig -p | grep libRmath
ldconfig -p | grep liblapack
ldconfig -p | grep libblas

Installing the package in R

Install the package in R using the devtools package.

library(devtools)
devtools::install_github("https://github.com/ashleyzhou972/PhiMRF")