Combine data from a typical DESeq2 run
wrapup_for_iSEE(dds, res)A DESeqDataSet() object.
A DESeqResults() object.
A SummarizedExperiment object, with raw counts, normalized counts, and variance-stabilizing transformed counts in the assay slots; and with colData and rowData extracted from the corresponding input parameters
Combines the DESeqDataSet input and DESeqResults into a SummarizedExperiment object, which can be readily explored with iSEE.
A typical usage would be after running the DESeq2 pipeline as specified in one of the workflows which include this package, e.g. in the context of the ideal package.
# with simulated data...
library(DESeq2)
dds <- DESeq2::makeExampleDESeqDataSet(n = 10000, m = 8)
dds <- DESeq(dds)
#> estimating size factors
#> estimating dispersions
#> gene-wise dispersion estimates
#> mean-dispersion relationship
#> final dispersion estimates
#> fitting model and testing
res <- results(dds)
se <- wrapup_for_iSEE(dds, res)
# library(iSEE)
# iSEE(se)
if (FALSE) { # \dontrun{
# or with the well known airway package...
library("airway")
data("airway", package = "airway")
airway
dds_airway <- DESeq2::DESeqDataSetFromMatrix(assay(airway),
colData = colData(airway),
design = ~ cell + dex
)
dds_airway <- DESeq2::DESeq(dds_airway)
res_airway <- DESeq2::results(dds_airway)
se_airway <- wrapup_for_iSEE(dds_airway, res_airway)
# iSEE(se_airway)
} # }