Please help, Deseq2 tool without replicates

Question

[kuttibiotech2009]

Dear sir,

I, Kamalakkannan R, am from the central university of Kerala. I am currently analysing the ovarian Transcriptomic data. But I haven't replicates for this data. Without this, I am facing a lot of problems. In this case, I am looking for your help. It will be helpful for my PhD work.

Using this code, I am getting 23k total expressions, 17k upregulated and 0 down-regulated. I don’t know why I am getting 0 downregulated genes. Please, sir, help me to complete part.

Thanks Sincerely
KAMALAKKANNAN R

#data from featureCount
countdata <- read.table("counts.txt",header = TRUE, skip = 1, row.names = 1)

head(countdata)

colnames(countdata) <- gsub(".bam", "", colnames(countdata), fixed = T)

colnames(countdata) <- gsub(".bam", "", colnames(countdata), fixed = T)

colnames(countdata) <- gsub("..", "", colnames(countdata), fixed = T)

countdata <- countdata[ ,c(-1:-5)]

head(countdata)

# sample  names
colData<-data.frame(condition=c("A","B"))
row.names(colData)<-c("A","B")
colData

library(DESeq2)
# generate  the  DESeqDataSet
ddsMat <- DESeqDataSetFromMatrix(countData = countdata,
                                 colData = colData,
                                 design = ~1)
# remove  genes  without  any  counts
DESeq.ds <- ddsMat[ rowSums(counts(ddsMat)) > 0, ]

colSums(counts(DESeq.ds)) 

ddsMat

# calculate  the  size  factor  and add it to the  data  set

DESeq.ds1 <- estimateSizeFactors(DESeq.ds)

sizeFactors(DESeq.ds1)

colData(DESeq.ds1)

counts.sf_normalized  <- counts(DESeq.ds1, normalized = TRUE)

dds <- DESeq(DESeq.ds1)

DGE.results  <- results(dds, independentFiltering = TRUE , alpha = 0.05)

summary(DGE.results)

write.csv(res2,"res2.csv")

[Asaf]

What is the structure of your data? Can you add a table with a list of the samples you have and their relevant metadata?

Answer 1

[ATpoint]

You cannot use DESeq2 without replicates. You are currently testing the intercept which has no meaning, see https://support.bioconductor.org/p/79209/

That is the line that makes no sense but it is the only design you can fit because as said, DESeq2 does not allow unreplicated designs:

ddsMat <- DESeqDataSetFromMatrix(countData = countdata,
                                 colData = colData,
                                 design = ~1)

Hence, you cannot use DESeq2 with your data.

Please use the search function and google. There are a lot of questions towards the "no replicate" situation.