0.99.12

Further reduced examples

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: pwrEWAS
 Title: A user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS) 
-Version: 0.99.11
+Version: 0.99.12
 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

@@ -9,32 +9,32 @@
 #' 
 #' @examples
 #' out = pwrEWAS(minTotSampleSize = 10,
-#'                    maxTotSampleSize = 20,
+#'                    maxTotSampleSize = 10,
 #'                    SampleSizeSteps = 10,
 #'                    NcntPer = 0.5,
-#'                    targetDelta = c(0.2, 0.5),
-#'                    J = 1000,
+#'                    targetDelta = 0.2,
+#'                    J = 100,
 #'                    targetDmCpGs = 10,
 #'                    tissueType = "Adult (PBMC)",
 #'                    detectionLimit = 0.01,
 #'                    DMmethod = "limma",
 #'                    FDRcritVal = 0.05,
 #'                    core = 2,
-#'                    sims = 30) 
+#'                    sims = 10) 
 #' pwrEWAS_powerPlot(data = out$powerArray, sd = FALSE)
 #' out = pwrEWAS(minTotSampleSize = 10,
-#'                    maxTotSampleSize = 20,
+#'                    maxTotSampleSize = 10,
 #'                    SampleSizeSteps = 10,
 #'                    NcntPer = 0.5,
-#'                    deltaSD = c(0.02, 0.03),
-#'                    J = 1000,
+#'                    deltaSD = 0.02,
+#'                    J = 100,
 #'                    targetDmCpGs = 10,
 #'                    tissueType = "Adult (PBMC)",
 #'                    detectionLimit = 0.01,
 #'                    DMmethod = "limma",
 #'                    FDRcritVal = 0.05,
 #'                    core = 2,
-#'                    sims = 30)
+#'                    sims = 10)
 #' pwrEWAS_powerPlot(data = out$powerArray, sd = TRUE)
 pwrEWAS_powerPlot <- function(data, sd = FALSE){
   sampleSizes <- as.numeric(dimnames(data)[[2]])

R/pwrEWAS_v1.7.R

@@ -29,7 +29,7 @@
 #'                    SampleSizeSteps = 10,
 #'                    NcntPer = 0.5,
 #'                    targetDelta = c(0.2, 0.5),
-#'                    J = 1000,
+#'                    J = 100,
 #'                    targetDmCpGs = 10,
 #'                    tissueType = "Adult (PBMC)",
 #'                    detectionLimit = 0.01,
@@ -43,7 +43,7 @@
 #'                    SampleSizeSteps = 10,
 #'                    NcntPer = 0.5,
 #'                    deltaSD = c(0.02, 0.03),
-#'                    J = 1000,
+#'                    J = 100,
 #'                    targetDmCpGs = 10,
 #'                    tissueType = "Adult (PBMC)",
 #'                    detectionLimit = 0.01,