Dear fellow researchers,
I am currently conducting experiments in which want to compare MFIs of wild-type mouse vs a mouse with mutation A. An example:
WT mouse 1 -> MFI = 1430
mutated mouse 1 -> MFI = 1389
fold change vs WT = 1389/1430 -> 0,9713
Then I conduct a t-test on the fold change values to see if they differ from 1.
In some experiments I took 2 pairs of mice (2 wild type and 2 with mutation A).
The mice in any specific experiment are all of the same gender and of the same age. An example:
WT mouse 1 -> MFI = 1430
WT mouse 2 -> MFI = 1415
mutated mouse 1 -> MFI = 1389
mutated mouse 2 -> MFI= 1521
How should these data be analyzed?
Option 1:
Calculation of the mean MFI of the WT mice
(1430+1415)/2 = 1422,5
Dividing the MFI of each one of the mutated mice with this value
fold change mutated mouse 1 : 1389/1422,5 = 0,9764
fold change mutated mouse 2 : 1521/1422,5 = 1,0692
Option 2:
Calculation of the mean MFI of the WT mice
(1430+1415)/2 = 1422,5
Calculation of the mean MFI of the mutated mice
(1521+1389)/2 = 1455
Dividing these MFIs
fold change = 1455/1422,5 = 1,0228
In this case I would put MFI data from mice A to first column and data from mice B to second column, then analyze it by Mann-Whitney (unpaired, nonparametric). GraphPad Prism will make your life easy.
In this case I would put MFI data from mice A to first column and data from mice B to second column, then analyze it by Mann-Whitney (unpaired, nonparametric).
If you have only 2 mice, you can make technical replicants, but this is not a good idea. The best will be increasing the numbers at least until 5.