Big Data Summer Institute 2019 | Genomics
bwolford@umich.edu
- Reproductive Research Demo
- Canvas
- Slack
- BDSI Wiki
- UNIX tutorial
- Useful UNIX one-liners
- Nano tutorial
- Download MobaXterm
- Data Visualization
- Graphical User Interface (GUI)
Enter the URL http://biostat-login.sph.umich.edu on Chrome or Firefox
Enter your password and complete Duo login
Interactive Apps >> RStudio
You can also submit jobs from here.
- Command line
Make sure you're on MWireless.
ssh <yourUNIQNAME>@biostat-login.sph.umich.edu
Enter your password and complete Duo login
You can use ssh -Y <yourUNIQNAME>@biostat-login.sph.umich.edu
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:
- submit a job using sbatch
- 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>@idran.bio.sph.umich.edu
ssh <uniqname>@bajor.bio.sph.umich.edu
#head to your home directory
cd ~/
#clone the repo
git clone https://github.com/bnwolford/BDSI.git
#move into the new folder that has been created
cd BDSI
Now you find yourself in a folder that mirrors the code and files in this repo.
Make a job array fil, for example some submit_jobs.sh
, 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 > submit_score.sh
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/create.slurm.scripts.opts.pl -f submit_jobs.sh -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>.slurm.sh
Execute that command. Check to see your jobs in the queue.
squeue -u <username>
Your questions answered here.
cd /home/bdsi2019/genomics/data/prs
To access code from the Zhou lab GitHub, you can clone the repo into your home directory.
cd ~/
git clone https://github.com/xzhoulab/DECComparison.git
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.
cd /home/bdsi2019/genomics/data/popgen
cd /home/bdsi2019/genomics/data/mr