Getting started

In this section, we outline the basic procedure to analyze your GWAS data with MendelIHT.

Installation

Download and install Julia. Within Julia, copy and paste the following:

using Pkg
pkg"add https://github.com/OpenMendel/SnpArrays.jl"
pkg"add https://github.com/OpenMendel/MendelIHT.jl"

MendelIHT.jl supports Julia 1.5+ for Mac, Linux, and window machines. A few features are disabled for windows users, and users will be warned when trying to use them.

Typical Workflow

Run cross_validate or cv_iht to determine best sparsity level (k).
Run iht or fit_iht on optimal k determined from cross validation.

We believe the best way to learn is through examples. Head over to the example section on the left to see these steps in action.

Parallel computing

Assuming you have 4 cores, one can load 4 processors by

Note

If you prefer to use the environment variable you can set it as follows in Bash (Linux/macOS):

export JULIA_NUM_THREADS=4

C shell on Linux/macOS, CMD on Windows:

set JULIA_NUM_THREADS=4

Powershell on Windows:

$env:JULIA_NUM_THREADS=4

Note that this must be done before starting Julia.

Also, the command BLAS.set_num_threads(1) is generally recommended to set the number of BLAS threads to 1, avoiding oversubscription

Running from command line as script

If you don't want to run MendelIHT.jl in a Julia session (e.g. you want to run batch jobs on a cluster), you can do so by putting the code below in a Julia file. For example, in order to run with 8 cores, create a file called iht.jl which contains:

# place these code in a file called iht.jl
using MendelIHT

# setup code goes here
plinkfile = ARGS[1]     # 1st command line argument (plink file location)
covariates = ARGS[2]    # 2nd command line argument (covariate file location)
path = 5:5:100          # test k = 5, 10, 15, ... 100

# run MendelIHT: first cross validate for best k, then run IHT using best k
mses = cross_validate(plinkfile, Normal, covariates=covariates, path=path)
iht_result = iht(plinkfile, Normal, k=path[argmin(mses)])

Then in the terminal you can do:

julia iht.jl plinkfile covariates.txt

You should get progress printed to your terminal and have cviht.summary.txt, iht.summary.txt, and iht.beta.txt files saved to your local directory