Get Started

Installation

To install julia, please go to the offical Julia website. Please see platform specific instructions if you have trouble installing Julia.

To install the package, use the following command inside the Julia REPL (or IJulia Notebook):

Pkg.add("JWAS")

To load the JWAS package, use the following command inside the Julia REPL (or IJulia Notebook):

using JWAS

The command Pkg.add("JWAS") will add the registered official JWAS package and dependencies.

To use the latest/beta features under development, run Pkg.add(PackageSpec(name="JWAS", rev="master")) to get the newest unofficial JWAS. Run Pkg.free("JWAS") to go back to the official one.

If you prefer “reproducible research”, an interactive Jupyter Notebook interface is available for Julia (and therefore JWAS). The Jupyter Notebook is an open-source web application for creating and sharing documents that contain live code, equations, visualizations and explanatory text. To install IJulia for Jupyter Notebook, please go to IJulia.

Docker

Jupyter Notebooks with JWAS via Docker

Docker provides a straightforward way to install Jupyter Notebooks with JWAS.

Install Docker from here for your platform.
From a terminal (on Mac or Linux), run the command:

docker run -it --rm -p 8888:8888 qtlrocks/jwas-docker

This will start a Jupyter Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token. Examples for JWAS can be accessed from the notebook: notebooks/0_index.ipynb.

The directories and files created within the Docker container will be lost when the container is stopped. To save your work on the host machine, a directory on the host machine can be mounted as a folder in the container with the -v option. After cd into your working directory on your local machine or a server, run the command

docker run -it --rm -p 8888:8888 -v `pwd`:/home/jovyan/work qtlrocks/jwas-docker

This command creates a Docker container with the folder /home/jovyan/work with the contents of pwd of the host machine. Files and directories that are in the folder pwd will not be lost when the container is stopped.

After running this command, it is expected to prompt something like

[I 10:41:54.774 NotebookApp] Writing notebook server cookie secret to /home/ubuntu/.local/share/jupyter/runtime/notebook_cookie_secret
[I 10:41:54.920 NotebookApp] Serving notebooks from local directory: /home/ubuntu
[I 10:41:54.920 NotebookApp] 0 active kernels
[I 10:41:54.920 NotebookApp] The Jupyter Notebook is running at:
[I 10:41:54.920 NotebookApp] http://0.0.0.0:8888/?token=75ad671f75b4c47be70591f46bec604997d8a9bd9dd51f0d
[I 10:41:54.920 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 10:41:54.921 NotebookApp]

    Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
        http://0.0.0.0:8888/?token=75ad671f75b4c47be70591f46bec604997d8a9bd9dd51f0d

Then, open the url in an internet browser (IE, Firefox, Chrome, Safari, etc) if JWAS-docker is launched on your local machine.

If you prefer running scripts using linux commands in Bash instead of Jupyter Notebook, please run the command

docker run -it --rm -v `pwd`:/home/jovyan/work qtlrocks/jwas-docker bash

Standalone application

standalone application (no installation required)

A fully self-contained application for JWAS (no installation required) will come out next year.

Access documentation

Warning

Please load the JWAS package at first.

To show the basic information (README file) of JWAS in REPL or IJulia notebook using ?JWAS and press enter.

For help on a specific function, type ? followed by its name, e.g. ?runMCMC and press enter in REPL or IJulia notebook.

The full documentation is available here.

Run your analysis

There are several ways to run your analysis.

(1) The easiest way to run analysis in Julia is by starting an interactive session (REPL) by double-clicking the Julia executable or running julia from the command line (e.g., terminal) as

julia> 1+2
3

julia> 3*4
12

To evaluate code written in a file script.jl in REPL, write and run

julia> include("script.jl").

To exit the interactive session, type ^D – the control key together with the d key or type quit().

(2) To run code in a file non-interactively from the command line (e.g.,termial), you can give it as the first argument to the julia command:

julia script.jl

If you want to pass arguments to your script, run it as

julia script.jl arg1 arg2

where arguments arg1 and arg2 are passed to your script as ARGS[1] and ARGS[2] of type String. Please see julia docs for more options.

(3) To run code in Jupyter Notebook, please see IJulia.

(4) To run code in Jupyter Notebook via Docker, please see Docker.