Last updated: 2020-06-24

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Knit directory: rss/

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This page shows how to install the Monte Carlo Markov chain (MCMC) scripts in rss/src/. In a standard computing environment with internet connection, the installation time is typically less than 10 minutes.

Step-by-step guide

0. Install git (optional)

To simplify Step 1 below, you may consider installing git in your computing environment (if it is not available there). Please see this excellent tutorial on installing git.

Please note that RSS software does not depend on git. You can complete Step 1 without installing git.

1. Clone rss repository

With git installed, you can easily clone rss by running the following command in Terminal.

git clone git@github.com:stephenslab/rss.git

Without git, you can manually download rss as follows.

wget https://github.com/stephenslab/rss/archive/master.zip
unzip master.zip
rm master.zip
mv rss-master rss

2. Download external packages

Download and install the lightspeed MATLAB toolbox (author: Tom Minka).

cd rss/src
wget http://ftp.research.microsoft.com/downloads/db1653f0-1308-4b45-b358-d8e1011385a0/lightspeed.zip
unzip lightspeed.zip
rm lightspeed.zip
cd lightspeed/
matlab -nodisplay < install_lightspeed.m

Download and install the lapack MATLAB package (author: Tim Toolan).

cd rss/src
unzip lapack.zip
rm lapackhelp.m lapack.zip license.txt

Note that if an appropriately compiled version of lapack.c does not exist, this package will ask whether to build one.

Download the progress MATLAB package (author: Martinho Marta-Almeida).

unzip progress.zip
rm progress.zip license.txt 

All downloaded files must be placed under rss/src.

-rw-rw-r-- 1 xiangzhu xiangzhu   5261 2015-11-11 08:46 calc_posterior_bvsr.m
-rw-rw-r-- 1 xiangzhu xiangzhu    972 2015-11-11 08:46 compute_pve.m
-rw-rw-r-- 1 xiangzhu xiangzhu  86772 2015-11-11 12:01 lapack.c
-rw-rw-r-- 1 xiangzhu xiangzhu   5927 2015-11-11 12:01 lapack.m
-rwxrwxr-x 1 xiangzhu xiangzhu 120123 2015-11-11 12:12 lapack.mexa64
drwx------ 6 xiangzhu xiangzhu  32768 2015-11-11 11:54 lightspeed
-rw-rw-r-- 1 xiangzhu xiangzhu   2573 2015-11-11 12:01 progress.m
-rw-rw-r-- 1 xiangzhu xiangzhu   4402 2015-11-11 08:46 propose_gamma.m
-rw-rw-r-- 1 xiangzhu xiangzhu  11629 2015-11-11 08:46 rss_ash.m
-rw-rw-r-- 1 xiangzhu xiangzhu  22182 2015-11-11 08:46 rss_bslmm.m
-rw-rw-r-- 1 xiangzhu xiangzhu   8363 2015-11-11 08:46 rss_bvsr.m
-rw-rw-r-- 1 xiangzhu xiangzhu  11348 2015-11-11 08:46 update_betatilde.m
-rw-rw-r-- 1 xiangzhu xiangzhu   4796 2015-11-11 08:46 update_bz.m
-rw-rw-r-- 1 xiangzhu xiangzhu  17205 2015-11-11 08:46 update_zlabel.m

Computing environment

Please note that RSS MCMC codes have only been extensively tested in the following environments.

  • version 8.4.0.150421 (R2014b) of MATLAB for 64-bit Linux

  • version 8.2.0.701 (R2013b) of MATLAB for 64-bit Linux

  • version 8.1.0.604 (R2013a) of MATLAB for 64-bit Linux

If you have any trouble installing RSS MCMC codes, please open an issue or email me (xiangzhu[at]uchicago[and/or]stanford.edu). To help me better understand your problems, please provide details of your computing environment.