Now I would like to know I have 50 normal and 50 cancer same sample numbers. How I find differentially expresssed genes in these two conditions.

condition <- cc('C1','C2'.....so on ,'N1','N2', and so on) file_list <- list.files(path = directory, pattern ="*.bam.count") sampleFiles <- c(file_list)

sampleTable <- data.frame(sampleName = sampleFiles, fileName = sampleFiles, condition = condition)

ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory2, design =~ condition) Warning message: In DESeqDataSet(se, design = design, ignoreRank) : some variables in design formula are characters, converting to factors

ddsHTSeq class: DESeqDataSet dim: 47051 100 metadata(1): version assays(1): counts rownames(47051): A1BG A1BG-AS1 ... ZZZ3 bA395L14.12 rowData names(0): colnames(100): C1.bam.count C10.bam.count ... N8.bam.count N9.bam.count colData names(1): condition

ddsHTSeq <- DESeq(ddsHTSeq)

estimating size factors estimating dispersions Error in checkForExperimentalReplicates(object, modelMatrix) :

The design matrix has the same number of samples and coefficients to fit,

so estimation of dispersion is not possible. Treating samples as replicates was deprecated in v1.20 and no longer supported since v1.

When I mentioned design =~ 1 in

ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory2, design =~ 1) Warning message: In DESeqDataSet(se, design = design, ignoreRank) : some variables in design formula are characters, converting to factors

ddsHTSeq class: DESeqDataSet dim: 47051 100 metadata(1): version assays(1): counts rownames(47051): A1BG A1BG-AS1 ... ZZZ3 bA395L14.12 rowData names(0): colnames(100): C1.bam.count C10.bam.count ... N8.bam.count N9.bam.count colData names(1): condition

ddsHTSeq <- DESeq(ddsHTSeq)

estimating size factors estimating dispersions ....................give the result.

Now please guide me how to differentiate among two samples from same organism. I will be heartily thankful to you.



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