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Generate an aggregate matrix of DESeqResults column values per contrast.

Usage

resultsMatrix(object, ...)

# S4 method for DESeqAnalysis
resultsMatrix(
  object,
  value = c("log2FoldChange", "stat", "alpha"),
  rowData = FALSE
)

# S4 method for DESeqAnalysisList
resultsMatrix(
  object,
  value = c("log2FoldChange", "stat", "alpha"),
  rowData = FALSE
)

Arguments

object

Object.

value

character(1). Value type to return. Corresponds to supported DESeqResults column:

  • log2FoldChange: log2 fold change.
    This will return shrunken LFC values if they are defined.

  • stat: Wald test statistic.

  • alpha: Either (1) padj, the BH adjusted P value; or (2) svalue, the s-value, when using apeglm (or ashr).

rowData

logical(1). Include row (gene) annotations, bound to the left side of the data frame.

...

Additional arguments.

Value

  • rowData = FALSE: matrix.

  • rowData = TRUE: DFrame.

Functions

  • resultsMatrix(DESeqAnalysisList): Loop across the nested DESeqAnalysis objects and aggregate the corresponding result matrices. Note that the analysis names are automatically prefixed to the column names.

Note

Updated 2022-05-17.

Examples

data(deseq)

## DESeqAnalysis ====
x <- resultsMatrix(deseq)
head(x)
#>       condition_B_vs_A treatment_D_vs_C
#> gene1      -0.22861748    -0.0033839310
#> gene2      -4.10817444    -0.0025026480
#> gene3      -0.35300593     0.0021734447
#> gene4      -0.25129296     0.0015954709
#> gene5       0.07545223    -0.0001299909
#> gene6       0.93641451     0.0066682954