Hi,

I'd like to calculate the increase in qualitative disease score per risk allele. I've a cohort of 1000, and a single SNP, for each of the individuals, I've a score from 0 to 100. It was recommended that I use a linear regression model.

Can anyone elaborate on why you might use a linear regression model for this? Are there any other models that would fit this task? Suggestions on R packages I could use, are welcome.

Thanks
The versions of linear regression (well, a linear model really) that you're familiar with are ANOVAs and T-tests. This is essentially an ANOVA, possibly with a partial factorial design (depending on how you want to set things up).

BTW, the alternative to this would be to divide the scores by 100 and use logistic regression. This would be to get around some ceiling and floor effects in more complex models. Of course, if you only have essentially two alleles then a Wilcoxon test (aka Mann-Whitney U-test) could work. But that only makes sense if you just have two groups. That's essentially just a non-parametric T-test.

Anyway, graph the data and have a look. Then fit it with lm() in R and plot that too to see if the fit seems reasonable.