Let's say I have a data frame of 1000 rows and 3 columns (column t0, t4 and t8). Each column represents a time point (0 hours, 4 hours and 8 hours). The data is gene expression: numeric (float):
row.name t0 t4 t8
ENSG00000000419.8 1780.00 1837.00 1011.00
ENSG00000000457.9 859.00 348.39 179.00
ENSG00000000460.12 1333.00 899.00 508.00
I need to normalize the data according to a known result. I know that the average half-life of all rows (genes) should be 10 hours. So I need to find the coefficients for t4 and t8 for which the average half life is 10 hours. The half-life for each row is calculated by the formula:
Half-life = 16 / (-2*log2(t4/t0)-log2(t8/t0))
You could say in principal the question is how to find coefficients for 2 of 3 columns given a known mean Y, a known formula and a known coefficient for the first column (1)? (I'm not a mathematician/statistician)
It's sort of a regression problem, no?
