A function to wrap up the DESeq2 inputs&outputs, and plug that as SingleCellExperiment into iSEE (original) (raw)
A function to wrap up the DESeq2 inputs&outputs, and plug that as SingleCellExperiment into iSEE
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| library(DESeq2) |
|---|
| wrapup_for_iSEE <- function(dds, res) { |
| # dds to vst |
| vst <- vst(dds) |
| # initialize the container |
| se <- SummarizedExperiment( |
| assays = List( |
| counts = counts(dds), |
| normcounts = counts(dds,normalized = TRUE), |
| vst_counts = assay(vst) |
| ) |
| ) |
| # adding colData, taken directly from the DESeqDataSet object |
| colData(se) <- colData(dds) |
| # extract contrast info |
| this_contrast <- sub(".*p-value: (.*)","\\1",mcols(res, use.names=TRUE)["pvalue","description"]) |
| # getting the rowData from the dds itself |
| rdd <- rowData(dds) |
| # modifying in advance the DESeqResults object |
| res$log10_baseMean <- log10(res$baseMean) |
| res$log10_pvalue <- -log10(res$pvalue) |
| # and for the rowData |
| rdd$log10_dispersion <- log10(rdd$dispersion) |
| # adding rowData to se |
| rowData(se)[[paste0("DESeq2_",gsub(" ","_",this_contrast))]] <- res |
| # merging in the existing rowData slot |
| rowData(se) <- cbind(rowData(se), rdd) |
| return(se) |
| } |
| # next, launch iSEE directly on the se object! |
| se <- wrapup_for_iSEE(dds,res) |
| library(iSEE) |
| iSEE(se) |