Last week I began analyzing genotype and phenotype data available through OpenSNP, a platform where people share this type of information.
The first phenotype I looked into was about smoking.
Using Python I took the smoker status reported by users and correlated it with a mutation (rs1051730) in the nicotinic acetylcholine receptor alpha 3 subunit CHRNA3 gene. A few genome wide association studies (GWAS) linked this mutation to nicotine dependence, alcohol abuse, and susceptibility of developing lung cancer.
My point with the post was to offer a proof of concept and to reveal/interpret the data I got out of my Python analysis. I wanted to create a precedent so that others could freely use and improve my scripts and my approach.
Of course, if you’re a user of OpenSNP, you can gain a lot of insight by looking at your own genotype for this SNP (single nucleotide polymorphism) and correlate it with my findings. To see the exact details of what I did and to download the Python codes, go and read the post.
Anyhow, I decided to continue with another analysis.