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Differential expression analysis with DESeq2

Hi all I am using HT-Seq count data to analyze differential expression with DESeq2 in R. I have about 60000 genes(all coding+non-coding genes) and 159 patients (two group, 0=66, 1=93). *Is this ok to use both coding and non-coding genes? or I should remove non-coding genes first? *Also, with DESeq2 I get this warning message. Is this effective on result or this is fine to have this warning? And how can I solve this?

rdata <- read.table("data.txt", header = TRUE, row.names = 1)

    library(DESeq2)

## Create metadata 
sample_org <- data.frame(row.names = colnames(rdata), c(rep("0", 66), rep("1", 93)))
colnames(sample_org) <- c("Group")

dds <- DESeqDataSetFromMatrix(countData = rdata,
                              colData = sample_org,
                              design = ~Group)


dd <- DESeq(dds)
res <- results(dd)
#Saving results
write.csv(res,"res.csv")

in this part I get warning:

dds <- DESeqDataSetFromMatrix(countData = rdata,
                         colData = sample_org,
                           design = ~Group)

The warning message is:

 Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
  some variables in design formula are characters, converting to factors
rna-seq

2 answers

Don't worry about the warning. Unless you want to use the metadata numerically, you want them to be factors.

just ignoring it. in most cases we need to set stringsAsFactors False to prevent unexpected error

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