Hello , Im doing a differential expresaion analysis and i want to compare 5 conditions with 3 biological replicates each, pairwise So there are 7 comoarisons i need to do. . So here is what I did once i got my counts matrix as cts. I dont know if the results I got are correct:

sampleTable< -data.frame(row.names=c("Bm14a","Bm14b","Bm14c","BTY14a","BTY14b","BTY14c","Mm14a","Mm14b","Mm14c","MTY14a","MTY14b","MTY14c","N14a","N14b","N14c"), condition=as.factor(c(rep("Bm14",3), rep("BTY14", 3), rep("Mm14", 3), rep("MTY14", 3),rep("N14", 3))))

dds <- DESeqDataSetFromMatrix(countData = cts,colData = sampleTable,design = ~ condition)

Pre-filtering:

dds <- dds[ rowSums(counts(dds)) > 1, ]

dds <- DESeq(dds)

All my comparisons: Comp_1<-results(dds, contrast=c("condition","N14","Bm14"))

Comp_2<-results(dds, contrast=c("condition","N14","BTY14"))

Comp_3<-results(dds, contrast=c("condition","N14","Mm14"))

and so on ... ... ...

Comp_7<-results(dds, contrast=c("condition","MTY14","Mm14"))

And to check the total diferentially expressed genes for each comparison i did the following for each Comp_n: Comp_1_resSig <- Comp_1[which(Comp_1$padj <0.1),]

head(Comp_1_resSig[order(Comp_1_resSig$log2FoldChange, decreasing = TRUE),])

nrow(Comp_1_resSig)

Is what I did correct? Are my results reliable? Are the p-values adjusted to each comparison? (I did not do a relevel because I read that for so many comparisons it wont make a difference)