I have RNAseq data of a experiment on cell lines as follows:
- 3 conditions: Control, TreatmentA, TreatmentB.
- 2 timepoints: 12h, 48h.
Initial assessment using pairwise comparisons between groups showed that both treatments up/down-regulate similar genes and pathways. However, the temporal dynamics between the 2 treatments are different.
I did also run a DESeq2 analysis using
design = ~ timepoint * treatment . This allows me to obtain the comparisons
timepoint48.treatmentB, both using control as the reference level.
I am interested in comparing the dynamics of the two treatments directly, using TreatmentA as the reference level.
However, I have doubts on the viability of such analysis: The samples are cancer cell lines kept in culture for 2 days. This causes even the control samples to show a ton of DEG between timepoints (794 down / 1002 up DEG). Thus, I want to study the temporal dynamics of the treaments, after removing the "changes through time" found in controls.
I am under the impression that, by running a design such as
design = ~ timepoint * treatment, the
timepoint part of the design is calculated on the reference level of the other variable. When using an interaction model with Control as the reference level for treatment, I get in
timepoint_48_vs_12 802 down / 1006 up DEG. That is pretty close to the results using a simple pairwise model comparing
Am I overthingking this? Is it possible to directly compare treatmentA vs treatmentB through time, but using only Control samples to correct for the "baseline effect" of time?
Should I limit my analysis to manually compare the results of
timepoint48.treatmentB when setting Control as the reference level?
Or, as the temporal changes in Control samples ought to be shared between TreatmentA and TreatmentB, when using one of the treatments as the reference level, any difference between treatments (shared with control) will be interesting by either inclusion or omission and treatment-specific ?
Thanks in advance