Short Course On The Genetics Of Addiction
- kallisto & EMASE (KB Choi & N Raghupathy): generate an index, pseudo-align reads and quantify the expression kallisto_emase_tutorial.sh
- DOQTL (D Gatti): kinship matrix, linkage and association mapping addiction_DOQTL_tutorial.Rmd
- DESeq2 (N Raghupathy): detect differential expression between groups of RNASeq samples DESeq2_tutorial.R
Docker is a lightweight container virtualization platform. We created two Docker images for this course: simecek/addictioncourse2015 (RStudio, DOQTL, DESeq2) and kbchoi/asesuite (kallisto, EMASE). You can run docker containers on your computer or in the cloud environments like AWS, Digital Ocean, Microsoft Azure or Google Cloud. Dockerfile can be also used as a list of instructions how to install the software on your computer.
How to start Digital Ocean droplet?
Here, I will give a description how our virtual machines have been created. You can either create a machine manually on Digital Ocean, SSH to it and start the docker containers. Or you can use R/analogsea package to start a droplet from a command line.
In both cases, first, create an account on Digital Ocean. You should get $10 promotional credit that currently corresponds to free 3.5 days of 8GB machine running expense.
For beginners - create a virtual machine manually
- Log into your Digital Ocean account. Click on "Create Droplet" button. Choose any droplet hostname and select its size - 8GB memory, 4 CPU, $0.119/hour.
Scroll down to "Select image", click on 'Applications' tab and select Docker. Click on "Create Droplet" button. Droplet now starts in 1-2 minutes. You should receive an email with a password.
- Note down your droplet's IP.ADDRESS. SSH into your droplet (
ssh root@DROPLET.IP.ADDRESS) and pull docker images
docker pull rocker/hadleyverse docker pull simecek/addictioncourse2015 docker pull kbchoi/asesuite
- Next, download required datasets (~30 minutes)
mkdir -p /sanger chmod --recursive 755 /sanger wget --directory-prefix=/sanger ftp://ftp-mouse.sanger.ac.uk/REL-1505-SNPs_Indels/mgp.v5.merged.snps_all.dbSNP142.vcf.gz.tbi wget --directory-prefix=/sanger ftp://ftp-mouse.sanger.ac.uk/REL-1505-SNPs_Indels/mgp.v5.merged.snps_all.dbSNP142.vcf.gz mkdir -p /kbdata chmod --recursive 755 /kbdata wget --directory-prefix=/kbdata ftp://ftp.jax.org/kb/individualized.transcriptome.fa.gz wget --directory-prefix=/kbdata ftp://ftp.jax.org/kb/rawreads.fastq.gz
- Finally, run docker containers. If you want to link it to your own data folder like
/mydatathen use additional
docker run -d -v /sanger:/sanger -p 8787:8787 -e USER=rstudio -e PASSWORD=rstudio simecek/addictioncourse2015 docker run -dt -v /sanger:/sanger -v /kbdata:/kbdata -p 8080:8080 kbchoi/asesuite
For advanced users - create a virtual machine with R/analogsea package
- Install R/analogsea package to your computer
- Create Digital Ocean API key and copy it to the second line of a script below
- Run the script
Access your virtual machine in the web browser
You are paying for your Digital Ocean machine as long as it is running. Do not forget to destroy it when you are done!