Hope you are well. I am running time course experiment to examine differentially expressed genes from tumour tissues between two conditions, radiotherapy and sham-radiotherpapy groups at 4 time points post radiotherapy. Each time point had size matched untreated controls. I used the following code to run model with interaction.
dds_all <- DESeqDataSetFromMatrix(countData = Raw.Count, colData = Phenotype, design = ~ Treatment + Time + Treatment:Time)
set reference group
dds_all$Treatment <- relevel(dds_all$Treatment, ref ="Sham-radiotherapy")
dds_all <- DESeq(dds_all)
resultsNames(dds_all) all_time_interaction <- results(dds_all, alpha =0.05) summary(all_time_interaction)
with this model, I got around 100 differentially expressed genes (not many)
dds_additive <- DESeqDataSetFromMatrix(countData = Raw.Count, colData = Phenotype, design = ~ Treatment + Time)
dds_additive$Treatment <- relevel(dds_additive$Treatment, ref ="Sham-radiotherapy")
dds_additive <- DESeq(dds_additive)
resultsNames(dds_additive) all_time_additive <- results(dds_additive,alpha = 0.05) summary(all_time_additive)
Additive model (no interaction) gave me around 3000 differentially expresse genes.
Hard to make a decision whether to retain the interaction or drop it because I did not see any p-value for interaction term? Does anyone knows where I can I look whether interaction is signficant? so I know whether I should keep it in the model or not? what is your suggestion to move forward!
I found tutorial using the following command to analyse Time course RNA seq using DEseqDataset function. I then tried it with my dataset using following command.
Time_course_RT <- DESeqDataSet(Raw.Count, ~ Treatment + Time + Treament:Time) Time_course_RT <- DESeq(Time_course_RT, test="LRT", reduced = ~ Treatment + Time)
My question is whether my option 1 using DESeqDataSetFromMatrix is correct to analyse Time course RNA seq compared with DEseqDataSet?
I got error once I used DEseqDataSet with the following message
*Error in DESeqDataSet(Raw.Count, ~Treatment + Time + Treament:Time) : 'se' must be a RangedSummarizedExperiment object*.
How do I fixed it? how could I convert my data into RangedSummarizedExperiment object ?
I found some people experienced this issue too, but did not get any definitive answer. Thank in advance for your help.