statistical justification of partitioning dataset for multiple analysis (EdgeR)

[seqse]

Dear all,

I'm doing analysis on allready mapped reads from sequencing data for differential expression with EdgeR. My experimental setup is as follow. I have samples from 4 different subjects. Material of each subject wast treated with 2 different treatments (and a control) for 2 timepoints.

I want to analyse the effect of the treatments (compared to control and compared to eachother)

In EdgeR I used following design
model.matrix(~ subject+ Treatment + Time +Treatment : Time)

I considered 2 strategies to analye te data:
Estimate parameters from above mentioned design with all data (all samples) and use different contrasts to get the differential expressed genes I want.

OR

Use only the samples of the two treatments (eg. control vs treatment1, treatment 1 vs treatment 2) I want to compare to fit the parameters. So using only 2/3 of all data. Repeat the previous 3 times till I have compared all 3 treatments with eachother. So exctually 3 different analysis using only a subset of the data.

I noticed that I could find considerably more significant differential expressed genes between 2 treatments with the last approach. But I wondered how correct this approach is? Will I have for example problems with multiple testing? (I control each analysis on fdr 5% with bejamin Hochberg)

thanks in advance
Kind regards