I would like to compare Q method against L method, and I have considered 2 different contrasts (at the end), but I am not sure which on is correct?
There are 2 different methods (Q and L) and from each one there are 2 biological replicates (L4,L6-L8 and Q3,Q5-Q7), and 2 technical replications from each biological replicate. as below:
design
biological_replicate method
L4_rep1 L4 L
L4_rep2 L4 L
L6_L8_rep1 L6_L8 L
L6_L8_rep2 L6_L8 L
Q3_rep1 Q3 Q
Q3_rep2 Q3 Q
Q5_Q7_rep1 Q5_Q7 Q
Q5_Q7_rep2 Q5_Q7 Q
design$biological_replicate <- factor(design$biological_replicate, levels = c("L4","L6_L8", "Q3", "Q5_Q7"))
design$method <- factor(design$method, levels = c("L", "Q"))
Group <- factor(paste(design$biological_replicate,design$method,sep="."))
design<- cbind(design,Group)
biological_replicate method Group
L4_rep1 L4 L L4.L
L4_rep2 L4 L L4.L
L6_L8_rep1 L6_L8 L L6_L8.L
L6_L8_rep2 L6_L8 L L6_L8.L
Q3_rep1 Q3 Q Q3.Q
Q3_rep2 Q3 Q Q3.Q
Q5_Q7_rep1 Q5_Q7 Q Q5_Q7.Q
Q5_Q7_rep2 Q5_Q7 Q Q5_Q7.Q
design.matrix <- model.matrix(~0+Group,design)
colnames(design.matrix) <- levels(Group)
my.contrasts_1 <- makeContrasts(QvsL = (Q3.Q+Q5_Q7.Q)/2-(L4.L+L6_L8.L)/2, levels = design.matrix)
my.contrasts_2 <- makeContrasts(QvsL = (Q3.Q+Q5_Q7.Q)-(L4.L+L6_L8.L), levels = design.matrix)
The contrasts are the same from a hypothesis testing perspective. I'd use the contrast 1 however (the difference between the averages) as the contrast coefficient that it returns will look like the difference on a log2 boxplot