0.99.16

including examples for plot functions again

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: pwrEWAS
 Title: A user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS) 
-Version: 0.99.15
+Version: 0.99.16
 Description: pwrEWAS is a user-friendly tool to assists researchers in the design and planning of EWAS to help circumvent under- and overpowered studies.
 Author: Stefan Graw
 Maintainer: Stefan Graw <sgraw@kumc.edu>

R/plotFunction_v1.4.R

@@ -8,8 +8,34 @@
 #' @export
 #' 
 #' @examples
-#' # pwrEWAS_powerPlot(data = outDelta$powerArray, sd = FALSE)
-#' # pwrEWAS_powerPlot(data = outSD$powerArray, sd = TRUE)
+#' outDelta = pwrEWAS(minTotSampleSize = 10,
+#'                    maxTotSampleSize = 20,
+#'                    SampleSizeSteps = 10,
+#'                    NcntPer = 0.5,
+#'                    targetDelta = c(0.2, 0.5),
+#'                    J = 1000,
+#'                    targetDmCpGs = 10,
+#'                    tissueType = "Adult (PBMC)",
+#'                    detectionLimit = 0.01,
+#'                    DMmethod = "limma",
+#'                    FDRcritVal = 0.05,
+#'                    core = 2,
+#'                    sims = 30)
+#' pwrEWAS_powerPlot(data = outDelta$powerArray, sd = FALSE)
+#' outSD = pwrEWAS(minTotSampleSize = 10,
+#'                    maxTotSampleSize = 20,
+#'                    SampleSizeSteps = 10,
+#'                    NcntPer = 0.5,
+#'                    deltaSD = c(0.02, 0.03),
+#'                    J = 1000,
+#'                    targetDmCpGs = 10,
+#'                    tissueType = "Adult (PBMC)",
+#'                    detectionLimit = 0.01,
+#'                    DMmethod = "limma",
+#'                    FDRcritVal = 0.05,
+#'                    core = 2,
+#'                    sims = 30)
+#' pwrEWAS_powerPlot(data = outSD$powerArray, sd = TRUE)
 pwrEWAS_powerPlot <- function(data, sd = FALSE){
   sampleSizes <- as.numeric(dimnames(data)[[2]])
   deltas <- dimnames(data)[[3]]
@@ -87,8 +113,34 @@ gg_color_hue <- function(n) {
 #' @export
 #' 
 #' @examples
-#' # pwrEWAS_deltaDensity(data = outDelta$deltaArray, detectionLimit = 0.01, sd = FALSE)
-#' # pwrEWAS_deltaDensity(data = outSD$deltaArray, detectionLimit = 0.01, sd = TRUE)
+#' outDelta = pwrEWAS(minTotSampleSize = 10,
+#'                    maxTotSampleSize = 20,
+#'                    SampleSizeSteps = 10,
+#'                    NcntPer = 0.5,
+#'                    targetDelta = c(0.2, 0.5),
+#'                    J = 1000,
+#'                    targetDmCpGs = 10,
+#'                    tissueType = "Adult (PBMC)",
+#'                    detectionLimit = 0.01,
+#'                    DMmethod = "limma",
+#'                    FDRcritVal = 0.05,
+#'                    core = 2,
+#'                    sims = 30)
+#' pwrEWAS_deltaDensity(data = outDelta$deltaArray, detectionLimit = 0.01, sd = FALSE)
+#' outSD = pwrEWAS(minTotSampleSize = 10,
+#'                    maxTotSampleSize = 20,
+#'                    SampleSizeSteps = 10,
+#'                    NcntPer = 0.5,
+#'                    deltaSD = c(0.02, 0.03),
+#'                    J = 1000,
+#'                    targetDmCpGs = 10,
+#'                    tissueType = "Adult (PBMC)",
+#'                    detectionLimit = 0.01,
+#'                    DMmethod = "limma",
+#'                    FDRcritVal = 0.05,
+#'                    core = 2,
+#'                    sims = 30)
+#' pwrEWAS_deltaDensity(data = outSD$deltaArray, detectionLimit = 0.01, sd = TRUE)
 pwrEWAS_deltaDensity <- function(data, detectionLimit = 0.01, sd = FALSE){
   maxDensY <- 0
   maxDensX <- 0