EIGENSOFT-Teaching: Difference between revisions

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=== Version ===
=== Version ===


6.1.4, 7.2.1
7.2.1


===Author / Distributor===
===Author / Distributor===
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Also refer to [[Running Jobs on the teaching cluster]]
Also refer to [[Running Jobs on the teaching cluster]]


*Version 6.1.4, installed in /usr/local/apps/eb/EIGENSOFT/6.1.4-foss-2016b
*Version 7.2.1, installed in /apps/eb/EIGENSOFT/7.2.1-foss-2019b


To use this version of EIGENSOFT, please first load the module with
To use this version of EIGENSOFT, please first load the module with
<pre class="gscript">
<pre class="gscript">
module load EIGENSOFT/6.1.4-foss-2016b
module load EIGENSOFT/7.2.1-foss-2019b
</pre>
 
*Version 7.2.1, installed in /usr/local/apps/eb/EIGENSOFT/7.2.1-foss-2016b
 
To use this version of EIGENSOFT, please first load the module with
<pre class="gscript">
module load EIGENSOFT/7.2.1-foss-2016b
</pre>  
</pre>  


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cd $SLURM_SUBMIT_DIR<br>
cd $SLURM_SUBMIT_DIR<br>
ml EIGENSOFT/7.2.1-foss-2016b<br>     
ml EIGENSOFT/7.2.1-foss-2019b<br>     
smartpca [options]<br>
smartpca [options]<br>
</div>
</div>
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<pre class="gcomment">
<pre class="gcomment">
module load EIGENSOFT/7.2.1-foss-2016b
module load EIGENSOFT/7.2.1-foss-2019b
smartpca
smartpca
no parameters
no parameters
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=== Installation ===
=== Installation ===
Version 6.1.4: Source code from https://www.hsph.harvard.edu/alkes-price/software/


Version 7.2.1: Source code from https://github.com/DReichLab/EIG/archive/
Version 7.2.1: Source code from https://github.com/DReichLab/EIG/archive/

Revision as of 22:36, 14 February 2021


Category

Bioinformatics

Program On

Teaching

Version

7.2.1

Author / Distributor

EIGENSOFT

Description

The EIGENSOFT package combines functionality from our population genetics methods (Patterson et al. 2006) and our EIGENSTRAT stratification correction method (Price et al. 2006). The EIGENSTRAT method uses principal components analysis to explicitly model ancestry differences between cases and controls along continuous axes of variation; the resulting correction is specific to a candidate marker’s variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. The EIGENSOFT package has a built-in plotting script and supports multiple file formats and quantitative phenotypes. More information: http://www.hsph.harvard.edu/alkes-price/software/

Running Program

Also refer to Running Jobs on the teaching cluster

  • Version 7.2.1, installed in /apps/eb/EIGENSOFT/7.2.1-foss-2019b

To use this version of EIGENSOFT, please first load the module with

module load EIGENSOFT/7.2.1-foss-2019b


Sample job submission script (sub.sh) to run version 7.2.1:


#!/bin/bash
#SBATCH --job-name=eigenjob
#SBATCH --partition=batch
#SBATCH --mail-type=ALL
#SBATCH --mail-user=username@uga.edu
#SBATCH --ntasks=1
#SBATCH --mem=4gb
#SBATCH --time=08:00:00
#SBATCH --output=eigenjob.%j.out
#SBATCH --error=eigenjob.%j.err

cd $SLURM_SUBMIT_DIR
ml EIGENSOFT/7.2.1-foss-2019b
smartpca [options]

where [options] need to be replaced by the options (command and arguments) you want to use.

In the real submission script, at least all the above underlined values need to be reviewed or to be replaced by the proper values.


Sample job submission command:

sbatch sub.sh


Documentation

module load EIGENSOFT/7.2.1-foss-2019b
smartpca
no parameters
## smartpca version: 16000

Installation

Version 7.2.1: Source code from https://github.com/DReichLab/EIG/archive/

System

64-bit Linux