Hello,
I have a RNASeq data from organoids derived from 4 patients. For one of the patients, the dataset includes organoids in two conditions, with and without treatment. Technical replicates were included for all organoids but these samples were collected at different timepoints (suffix P + number refer to this timepoints) to reduce variability due to routine organoid care when changing culture media. In addition, I have 3 different batches. Here is the design.
Sample_name Treatment Patient Replicate Batch
mCTO50BP2 No 5 1 run1
mCTO50BP5 No 5 2 run1
mCTO50BP9 No 5 3 run1
mCTO50P2 Yes 5 1 run1
mCTO50P3 Yes 5 2 run1
mCTO50P6 Yes 5 3 run1
mCTO66S3-P3 No 6 1 run2
mCTO66S3-P7 No 6 2 run2
mCTO66S3-P9 No 6 3 run2
RTO2P5 No 8 1 run1
RTO2P8 No 8 2 run1
RTO7P2 No 9 1 run1
RTO7P7 No 9 2 run1
RTO7-P10 No 9 3 run3
My questions: 1) To perform multiple comparisons
1a .- mCTO50 vs mCTO50B
1b.- (RTO2 + RTO7 + mCTO50) vs (mCTO50B + mCTO66S3)
1c.- RTO7 vs (RTO2+mCTO66S3+mCTO50+mCTO50B)
Should I load into DESeq2 all the samples in the same matrix, construct one model and then perform different contrasts or should I load just the samples that I want to analyze together one at a time?
2) To compare the organoids of patient 5 between them (Treatment Yes Vs Treatment No), and explore the differences in transcription for this patient (what some authors name "personalome"), would it be fine if I treat each of these samples as independent samples, i.e., not collapsing the replicates?
Thanks very much in advance.
Best regards,
Sheila