Reshape DE-SWAN output

Reshape DE-SWAN output

reshape.DEswan(res.DEswan, parameter, factor)

Arguments

res.DEswan:	a data Frame - output from DEswan
parameter:	an optional numeric - 1 for pvalue or 2 for coefficients. Default is 1
factor:	an optional character string - qt or covariates in DEswan. Default is qt.

Examples

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"
head(res.DEswan$p)
#>    variable window.center factor      pvalue
#> 1 Feature_1            40     qt 0.479188190
#> 2 Feature_1            40    Sex 0.064129958
#> 3 Feature_1            40 Cohort 0.002082943
#> 4 Feature_2            40     qt 0.818757036
#> 5 Feature_2            40    Sex 0.106665375
#> 6 Feature_2            40 Cohort 0.116499806
head(res.DEswan$coeff)
#>                           variable window.center        factor  coefficient
#> (Intercept)              Feature_1            40   (Intercept)  3.482908497
#> qt.tmp1                  Feature_1            40            qt  0.035679739
#> covariates$SexMale       Feature_1            40       SexMale  0.103411765
#> covariates$CohortSeattle Feature_1            40 CohortSeattle -0.310418301
#> (Intercept)1             Feature_2            40   (Intercept)  2.723666667
#> qt.tmp11                 Feature_2            40            qt -0.006666667
res.DEswan.wide.p=reshape.DEswan(res.DEswan)
res.DEswan.wide.p=reshape.DEswan(res.DEswan,parameter = 1,factor = "qt")
head(res.DEswan.wide.p)
#>       variable       X40       X50       X60        X70        X80        X90
#> 1    Feature_1 0.4791882 0.3541882 0.8709966 0.29133843 0.74820898 0.01970705
#> 2   Feature_10 0.1162009 0.7176725 0.2721085 0.91346294 0.95392551 0.52132819
#> 3  Feature_100 0.7319143 0.3916739 0.4446613 0.02942558 0.92130404 0.23809419
#> 4 Feature_1000 0.5580754 0.6749681 0.9434219 0.08057361 0.06311563 0.67770017
#> 5 Feature_1001 0.4504957 0.3772323 0.9570524 0.16085845 0.14049569 0.16085304
#> 6 Feature_1002 0.4394018 0.5707327 0.6723199 0.88106601 0.19342936 0.02351984
#>         X100
#> 1 0.06799034
#> 2 0.27758491
#> 3 0.72850088
#> 4 0.04381452
#> 5 0.24115589
#> 6 0.72922219
res.DEswan.wide.coeff=reshape.DEswan(res.DEswan,parameter = 2,factor = "qt")
head(res.DEswan.wide.coeff)
#>       variable         X40         X50          X60          X70          X80
#> 1    Feature_1  0.03567974 -0.03608333  0.005070894  0.027445010  0.010427003
#> 2   Feature_10 -0.15054902 -0.01551075 -0.024238119  0.002680289  0.001652225
#> 3  Feature_100  0.01695425  0.04031452  0.023230858  0.064358827 -0.003223627
#> 4 Feature_1000  0.12998693 -0.06021237  0.007353487 -0.190922080  0.307072058
#> 5 Feature_1001 -0.23228758 -0.10303226  0.001522927  0.126873135 -0.210616030
#> 6 Feature_1002  0.13012418 -0.05818280  0.026896544 -0.009067305  0.080272994
#>           X90        X100
#> 1 -0.09822113 -0.07817499
#> 2  0.02253488  0.05498679
#> 3  0.07810322 -0.02613265
#> 4  0.05848103 -0.29391676
#> 5  0.12023256 -0.11623561
#> 6 -0.15629294 -0.01380438