Hello,

I want to gather all DESeq functions in a custom function and then plan to connect with visualization part. Then will call this "DEG_analysis" function in apply function to do multiple runs in loop-like format.

This is an example of my colData design;

> colData[1:3,1:3]
        X ABT737 Afatinib
1   BT-20      R        R
2 CAL-120      S        R
3  CAL-51      R        R

> dim(colData)
[1] 17 53

I cannot make DESeqDataSetFromMatrix function to recognize "i" as a design to generate "dataset" for down-stream of DESeq2.My question is, how can I make interested column names ("i") to be recognized as a variable in design = ~i or something similar to this concept?

DEG_analysis <- function(i)
    {
      colData_tmp <- as.data.frame(colData %>%  select("X", i))
      colData_tmp[,2] <- as.factor(colData_tmp[,2])
      dataset <- DESeqDataSetFromMatrix(countData = countData,colData = colData_tmp,design = ~paste0(i))
      dds <- DESeq(dataset,minReplicatesForReplace = Inf)
      vsd <- vst(dds,blind = F)
      results_tmp <- results(dds, contrast=c(i, "R", "S"),cooksCutoff = T, independentFiltering=T, pAdjustMethod = "bonferroni", alpha = 0.05)
      results_tmp <- results_tmp[order(results_tmp$padj),]
    ....
    }

Currently, I am taking this error message:

Error in DESeqDataSet(se, design = design, ignoreRank) : 
  all variables in design formula must be columns in colData

If I'm reading correctly, you want to convert a string to a formula to pass as an argument to design? See ?formula. E.g. formula("~x")

What you are asking is probably too much to cram into one function.

Start with one function into which you give an object, a design, and a list of (contrast, factor1, factor2, comparisonName) for all the comparisons you want. This way, you only do DESeq one for multiple comparisons, and you can do more complicated designs than just the column header.

Once you have that, you can work on automating the process that generates that input.