q.DEswan.Rdcaculate qvalues for DE-SWAN output
q.DEswan(res.DEswan.wide, method)
| res.DEswan.wide.p: | a data Frame - pvalues from DEswan in a wide format |
|---|---|
| method: | method for pvalues adjustment. Default is BH |
res.DEswan=DEswan(data.df = agingplasmaproteome[,-c(1:3)], qt = agingplasmaproteome[,1], window.center = seq(40,100,10), buckets.size = 10, covariates = agingplasmaproteome[,c(2:3)])#> [1] "window.center 1/7" #> [1] "window.center 2/7" #> [1] "window.center 3/7" #> [1] "window.center 4/7" #> [1] "window.center 5/7" #> [1] "window.center 6/7" #> [1] "window.center 7/7"res.DEswan.wide.p=reshape.DEswan(res.DEswan,parameter = 1,factor = "qt") res.DEswan.wide.q=q.DEswan(res.DEswan.wide.p,method="BH") head(res.DEswan.wide.q)#> variable X40 X50 X60 X70 X80 X90 #> 1 Feature_1 0.9563654 0.9917277 0.9996536 0.6623635 0.8713017 0.3859296 #> 2 Feature_10 0.9563654 0.9917277 0.9996536 0.9580174 0.9701435 0.9328920 #> 3 Feature_100 0.9622163 0.9917277 0.9996536 0.4413837 0.9609768 0.7743029 #> 4 Feature_1000 0.9563654 0.9917277 0.9996536 0.5038775 0.2473830 0.9646899 #> 5 Feature_1001 0.9563654 0.9917277 0.9996536 0.5582810 0.3854607 0.7067785 #> 6 Feature_1002 0.9563654 0.9917277 0.9996536 0.9521774 0.4647609 0.4132851 #> X100 #> 1 0.5281392 #> 2 0.8232916 #> 3 0.9355416 #> 4 0.4479155 #> 5 0.8008478 #> 6 0.9355416