如何构建数据集以随时间运行计数比的二项式 GLM？

Question

I am trying to do an analysis using a binomial GLM to test for differences in relative count frequency over time (Days). The GLM model/formula would look something like this:

(1:2) ∼ Day

Where we are testing for the effect of Day on the frequency of A1:A2. Basically this is a binomial generalized linear model where A1 and A2 refer to the read counts of alternative alleles at each gene and Day is a multilevel factor. The other thing is that I would be testing this on many different genes (100's) so that we would be doing many tests.

The basic model formula in R is straightforward (eg using a long format dataset): `

glm(AF1:AF2 ~ Day, data = dfLong, family = "binomial")

But Im not really sure how to structure the data or loop over the Gene variable to accomplish this task?

Here is an example dataframe:

> df<-read.csv("test.csv")
> df
  Gene A.count_1 A.count_2 Day
1    1        60        40   1
2    2       100        30   1
3    3       100         3   1
4    1        55       100   3
5    2       423       410   3
6    3       191        89   3
7    1        20        10   5
8    2       200        10   5
9    3       100        20   5

The output I'd like is the test of the effect of Day as a factor (not a numeric variable) on allele count ratios for each gene, producing a p-value for each gene (eg 1,2, and 3, or more, 100s, in the general case).

Any help to set me in the right direction would be mnuch appreciated.

Thanks!!

Answer 1

I think that

library('lme4')
m <- lmList(AF1:AF2 ~ Day | Gene, data = dfLong, family = "binomial")
summary(m)

should probably do it?