Summarise DMRs by contrast

Count the number of up- and down-regulated DMR windows per contrast. Internally, results are reshaped to long format before summarisation.

summariseDMRsByContrast(
  DMRtable,
  FDRthres = 0.05,
  log2FCthres = 0,
  deltaBetaThres = 0
)

Arguments

DMRtable

data.frame or GRanges DMR results, typically returned by calculateDMRs(). If in wide format, it will be converted with pivotDMRsLonger().

FDRthres

numeric(1) False discovery rate threshold for significance. Default: 0.05.

log2FCthres

numeric(1) Absolute log2 fold-change threshold for calling up/down regulation. Default: 0.

deltaBetaThres

numeric(1) Absolute delta-beta threshold for calling up/down regulation. Default: 0.

Value

A tibble:

• summariseDMRsByContrast(): returns one row per contrast, with counts of up-regulated (nUp) and down-regulated (nDown) DMRs that pass the specified thresholds.

See also

pivotDMRsLonger(), summariseDMRsByGene()

Other DMR-helpers: pivotDMRsLonger(), summariseDMRsByGene(), writeDMRsToBed(), writeDMRsToExcel()

Examples

data(exampleTumourNormal, package = "mesa")

# Summarise DMRs for a single contrast, using custom FDR threshold
exampleTumourNormal %>%
    calculateDMRs(
        variable = "type",
        contrasts = "LUAD_vs_NormalLung",
        FDRthres = 0.1
    ) %>%
    summariseDMRsByContrast(FDRthres = 0.1)
#> Generating table of nrpm values for 819 regions across 5 samples.
#> Fitting initial GLM on 255 windows, without using parallelisation.
#> Performing contrast LUAD_vs_NormalLung
#> Contrasts Complete
#> selecting regions from contrast LUAD_vs_NormalLung
#> selected 58/255 windows
#> adding test results from LUAD_vs_NormalLung
#> # A tibble: 1 × 4
#>   group1 group2       nUp nDown
#>   <chr>  <chr>      <int> <int>
#> 1 LUAD   NormalLung    56     2