@@ -96,7 +96,7 @@

 #'                        TCGA_GBM_miRNA_microarray)

 #' @export

 discordantRun <- function(v1, v2, x, y = NULL, transform = TRUE, 

-                          subsampling = FALSE, subSize = dim(x)[1], iter = 100, 

+                          subsampling = FALSE, iter = 100, 

                           components = 3) {

     .checkDiscordantInputs(v1, v2, x, y, transform, subsampling, subSize, iter, 

@@ -124,42 +124,15 @@ discordantRun <- function(v1, v2, x, y = NULL, transform = TRUE,

     }

     if (subsampling) {

-        subSize <- min(nrow(x), nrow(y))

+        subSize = .setSubSize(x, y)

         total_mu <- total_sigma <- total_nu <- 

           total_tau <- total_pi <- rep(0, components)

         for(i in 1:iter) {

-            # make sure pairs are independent

-            rowIndex <- sample(nrow(x), subSize)

-            

-            if(is.null(y)) {

-              # colIndex <- sample(nrow(x), subSize)

-              sampleNames <- rownames(x)

-              

-              if (floor(length(sampleNames) / 2) < subSize) {

-                warning("Provided subSize too high. Using number of features divided by 2.")

-                subSize <- floor(length(sampleNames) / 2)

-              }

-              

-              nameSet1 <- sample(sampleNames, subSize)

-              nameSet2 <- setdiff(sampleNames, nameSet1)

-              nameSetA <- paste0(nameSet1, "_", nameSet2)

-              nameSetB <- paste0(nameSet2, "_", nameSet1)

-              subSampV1 <- ifelse(is.na(v1[nameSetA]), v1[nameSetB], v1[nameSetA])

-              subSampV2 <- ifelse(is.na(v2[nameSetA]), v2[nameSetB], v2[nameSetA])

-            } else {

-              colIndex <- sample(nrow(y), subSize)

-              mat1 <- matrix(v1, nrow = nrow(x), byrow = FALSE)

-              mat2 <- matrix(v2, nrow = nrow(x), byrow = FALSE)

-              subSampV1 <- sapply(1:subSize, function(x) mat1[rowIndex[x], 

-                                                              colIndex[x]])

-              subSampV2 <- sapply(1:subSize, function(x) mat2[rowIndex[x], 

-                                                              colIndex[x]])

-            }

-            

-            sub.pdata <- cbind(subSampV1, subSampV2)

-            sub.class <- cbind(.assignClass(subSampV1, param1, components),

-                               .assignClass(subSampV2, param2, components))

+            subSamples <- .createSubsamples(x, y, v1, v2, subSize)

+            sub.pdata <- cbind(subSamples$v1, subSamples$v2)

+            sub.class <- cbind(.assignClass(subSamples$v1, param1, components),

+                               .assignClass(subSamples$v2, param2, components))

             pd <- em.normal.partial.concordant(sub.pdata, sub.class, components)

             total_mu <- total_mu + pd$mu_sigma[1,]

@@ -282,9 +255,29 @@ em.normal.partial.concordant <- function(data, class, components) {

   return(rtn)

 }

-# .createSubsamples <- function(x, y = NULL, v1, v2) {

-#   

-# }

+.createSubsamples <- function(x, y = NULL, v1, v2, subSize) {

+  if(is.null(y)) {

+    sampleNames <- rownames(x)

+    nameSet1 <- sample(sampleNames, subSize)

+    nameSet2 <- sample(setdiff(sampleNames, nameSet1))

+    nameSetA <- paste0(nameSet1, "_", nameSet2)

+    nameSetB <- paste0(nameSet2, "_", nameSet1)

+    subSampV1 <- ifelse(is.na(v1[nameSetA]), v1[nameSetB], v1[nameSetA])

+    subSampV2 <- ifelse(is.na(v2[nameSetA]), v2[nameSetB], v2[nameSetA])

+  } else {

+    # make sure pairs are independent

+    rowIndex <- sample(nrow(x), subSize)

+    colIndex <- sample(nrow(y), subSize)

+    mat1 <- matrix(v1, nrow = nrow(x), byrow = FALSE)

+    mat2 <- matrix(v2, nrow = nrow(x), byrow = FALSE)

+    subSampV1 <- sapply(1:subSize, function(x) mat1[rowIndex[x], 

+                                                    colIndex[x]])

+    subSampV2 <- sapply(1:subSize, function(x) mat2[rowIndex[x], 

+                                                    colIndex[x]])

+  }

+  return(list(v1 = subSampV1,

+              v2 = subSampV2))

+}

 # Internal function to validate user inputs for discordantRun()

 #' @importFrom methods is

@@ -302,12 +295,12 @@ em.normal.partial.concordant <- function(data, class, components) {

   # }

   if (!(components %in% c(3, 5))) {

-    stop ("components must be equal to 3 or 5")

+    stop ("Components must be equal to 3 or 5")

   }

   if (transform && (range(v1)[1] < -1 || range(v1)[2] > 1 || 

                     range(v2)[1] < -1 || range(v2)[2] > 1)) {

-    stop ("correlation vectors have values less than -1 and/or greater than 1.")

+    stop ("Correlation vectors have values less than -1 and/or greater than 1.")

   }

 }

@@ -320,6 +313,16 @@ em.normal.partial.concordant <- function(data, class, components) {

   if(any(c(sumZx, sumZy) == 0)) {

     stop("Insufficient data for component estimation. Increase number of 

          features or reduce number of components used. If subsampling=TRUE,

-         consider increasing subSize as well.")

+         you may need set subsampling=FALSE.")

+  }

+}

+

+# Internal function to set sub size based on data

+.setSubSize <- function(x, y) {

+  if (is.null(y)) {

+    sampleNames <- rownames(x)

+    subSize <- floor(length(sampleNames) / 2)

+  } else {

+    subSize <- min(nrow(x), nrow(y))

   }

 }

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