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BDSI | Genomics

Big Data Summer Institute 2019 | Genomics


Log into compute resources

  1. Graphical User Interface (GUI)

Enter the URL on Chrome or Firefox
Enter your password and complete Duo login
Interactive Apps >> RStudio You can also submit jobs from here.

  1. Command line

Make sure you're on MWireless. ssh <yourUNIQNAME>
Enter your password and complete Duo login You can use ssh -Y <yourUNIQNAME> so that you can open figures interactive when you're running R from the command line. If you want to request resources for a long-running or memory intensive command, you will need to:

  1. submit a job using sbatch
  2. request an interactive job on a compute node using srun
    srun --time=2:00:00 --mem=2GB --pty /bin/bash

If you want to log specifically into one of the login nodes. For example, you might want to run htop in the same login node that you are running a process.

ssh <uniqname>  
ssh <uniqname>  

Access this repository from your home directory

#head to your home directory
cd ~/
#clone the repo
git clone
#move into the new folder that  has been  created

Now you find yourself in a folder that mirrors the code and files in this repo.

Submit job array via the command line

Make a job array fil, for example some, with one command per line. For example:

for f in `ls /tmp/bdsi2019/genomics/data/prs/gfg/*snps.bim`; do base=`basename $f .bim`; echo “plink --bfile /tmp/bdsi2019/genomics/data/prs/gfg/$base --score --out $base”; done >

And if you cloned this repo into your home directory (see the 'Access this respository from home directory' section above) you can execute a command as follows, customizing memory, time, cpu, etc.
perl ~/BDSI/ -f -m 2 -t 12:00:00 -j <name> -c 1
This script will tell you to run something like this
sbatch /home/bdsi2019/genomics/data/prs/gfg/<name>
Execute that command. Check to see your jobs in the queue.
squeue -u <username>


Your questions answered here.

Project-specific notes

Polygenic risk scores

cd /home/bdsi2019/genomics/data/prs

Single Cell RNAseq

To access code from the Zhou lab GitHub, you can clone the repo into your home directory.
cd ~/
git clone
cd DECComparison

We want to practice a typical workflow which involves sharing a cenral dataset and performing indpendent analyses in our own directories. For this reason, I've downloaded the data for you, and those steps are now commented out (i.e. # is placed at the front of the code line).

We want to start an interactive session to request compute resources before we get started.
srun --time=2:00:00 --mem=2GB --pty /bin/bash
In an analysis directory in your home directory, launch R with R. Follow the R code and answer the questions here.

Population Genetics

cd /home/bdsi2019/genomics/data/popgen

Mendelian Randomization

cd /home/bdsi2019/genomics/data/mr


Big Data Summer Institute 2019






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