Assigning Significance To Variants In Two Populations
I have two groups of people, a healthy population which has carriers of disease and non-carriers and I have a sick population. I know the frequency of genetic variants in both groups. I want to know if I can say anything about the variants with any statistical certainty and how would I do that.
Variant Frequency in Healthy Population Frequency in Sick Population
X 30 25
Y 5 700
Z 600 600
Each group(Healthy and Sick) has 1000 people in it. Can I say anything about each variant?
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For variants X and Y, for example, using R:
> fisher.test(matrix(c(30,970,25,975),nc=2))
Fisher's Exact Test for Count Data
data: matrix(c(30, 970, 25, 975), nc = 2)
p-value = 0.5848
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.6800755 2.1559989
sample estimates:
odds ratio
1.206071
> fisher.test(matrix(c(5,995,300,700),nc=2))
Fisher's Exact Test for Count Data
data: matrix(c(5, 995, 300, 700), nc = 2)
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.003770656 0.027915933
sample estimates:
odds ratio
0.01175757
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sure. chi-square test, binomial test and many many more. Also, these numbers are not frequencies, they are counts.
Sorry, should have said counts. Thanks!
lol no worries. [R] has all the machinery for you. you can do a chi-square matrix(3*2), ref count / alt count for all groups.
What would go in the matrix?