Hi, I have a question about the best practice design for my dataset.

I have total 300 samples with

• Medicine group: 150 samples (75 pre-treatment, 75 post-treatment)

• Placebo group: 150 samples (75 pre-placebo, 75 post-placebo)

My goal is to determine whether medicine has a treatment effect compared to placebo. My samples have following characteristics:

1. Generally low sequencing depth, which initially produced a winged volcano plot due to high variability in low-count genes

2. PCA analysis (using RSEM TPM values) revealed the following covariates:

• PC1: Batch effects
• PC2: Age
• PC2 + PC3: Pre/post treatment timing (regardless of medicine vs. placebo)

Therefore, I designed a DESeq2 interaction model including the covariates (paired sample information, batch, sex, age). The code is shown below. However, I'm encountering a "model matrix not full rank" error. While I found some guidance online for resolving this issue, I'm not confident my overall design is appropriate for my case. Could you provide advice on the best way to analyze this paired treatment dataset?

library(DESeq2)
countData <- read.csv('count.csv', row.names=1, check.names=FALSE)
colData <- read.csv("meta.csv", row.names=1)
countData <- round(countData)
colData$subject_id <- factor(colData$subject_id)
colData$batch <- factor(colData$batch)
colData$sex <- factor(colData$sex)
colData$age <- as.numeric(colData$age)
colData$age <- scale(colData$age) # Center and scale the age variable
colData$time <- factor(colData$time, levels = c("pre", "post")) # pre as reference
colData$condition <- factor(colData$condition, levels = c("Placebo", "Medicine")) # Placebo as reference
dds <- DESeqDataSetFromMatrix(countData = countData,
colData = colData,
design = ~ subject_id(paired_sample info) + batch + sex + age + time(pre/post) + condition(placebo/medicine) + time:condition
keep <- rowSums(counts(dds) >= 10) >= 30 # %10 of my total samples. Might be bit strigent?
dds <- dds[keep,]
dds <- DESeq(dds)
res <- results(dds, name = "timepost.conditionDFO")

Thanks for your help

Regards,

Junmo