I am using DEseq2 to do differential analysis from RNA-seq data across 4 developmental stages, each stages have 2 replicates. I can following through the manual to do comparisons between each two stages. Now I want to do the comparison across 4 stages in a time series manner so that I can know the genes that have the expression level either all the way up or down or no obvious trend.
I searched the manual and questions posted: in the manual, it usually has two conditions eg
design= ~strain+minute or different treatments at different time points, mine have only 1 condition:
I directly generated the deseqDataset in this way:
ddsMat <- DESeqDataSetFromMatrix(countData = countdata, colData = coldata, design = ~ time) dds <- ddsMat dds #explore sample relationships, this is not the step for differential analysis nrow(dds) dds <- dds[rowSums(counts(dds)) > 1,] # remove the sample that reads from all group are 0
Then I typed:
ddsTC <- DESeq(dds, test = "LRT", reduced = ~time)
But I got the error:
> estimating size factors estimating dispersions gene-wise dispersion > estimates mean-dispersion relationship final dispersion estimates > fitting model and testing Error in nbinomLRT(object, full = full, > reduced = reduced, quiet = quiet, : less than one degree of > freedom, perhaps full and reduced models are not in the correct order
I searched around and in most situations the answer is advising to consult the statistician without solution to this problem. I am wondering is there a way to make it work and get a chance to see the results?