[b]#Load data[/b]
counts=read.csv("F:/data.csv", row.names=1, header=TRUE, check.names=FALSE)
[b]#converting counts to integer mode[/b]
colData = data.frame(condition=c("A1","A2","A3","A4","A5","A6"), row.names = colnames(counts))
dds <- DESeqDataSetFromMatrix(countData = round(counts), colData = colData, design = ~ condition)
[b]#Pre-filtering the dataset[/b]
dds <- dds[ rowSums(counts(dds)) > 1, ]
[b]#Normalization[/b]
rld <- rlog(dds, blind = FALSE)
这里就开始出错了，
Error in estimateDispersionsGeneEst(object, quiet = TRUE) :
the number of samples and the number of model coefficients are equal,
i.e., there are no replicates to estimate the dispersion.
use an alternate design formula
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