@@ -14,7 +14,7 @@

 #' data(SimpSim)

 #' createscCoGAPSSets(SimpSim.D, SimpSim.S, nSets=2, "example")

 #' @export

-createscCoGAPSSets <- function(D, S, nSets, simulationName,samplingRatio=NULL,path="")

+createscCoGAPSSets <- function(D, nSets, simulationName,samplingRatio=NULL,path="")

 {

     # check gene names

     if (length(unique(colnames(D))) != length(colnames(D)))

@@ -41,7 +41,10 @@ createscCoGAPSSets <- function(D, S, nSets, simulationName,samplingRatio=NULL,pa

         # partition data

         sampleD <- D[,cellset]

-        sampleS <- S[,cellset]

+        #log transform 

+        sampleD <- log2(sampleD+1)

+        # generate S

+        sampleS <- pmax(.1*sampleD, .1)

         save(sampleD, sampleS, file=paste0(path,simulationName, "_partition_", set,".RData"));

     }

     return(simulationName)

new file mode 100644

@@ -0,0 +1,28 @@

+#' Post Processing of Parallel Output

+#'

+#' @param AP.fixed output of parallel gapsMapRun calls with same FP

+#' @param setPs data.frame with rows giving fixed patterns for P used as input

+#' for gapsMapRun

+#' @return list of two data.frames containing the A matrix estimates or their

+#' corresponding standard deviations from output of parallel CoGAPS

+postFixed4SC <- function(AP.fixed, setAs)

+{

+    ASummary <- AP.fixed[[1]]$Amean

+

+

+    PSummary <- do.call(cbind,lapply(AP.fixed, function(x) x$Pmean))

+    Psd <- do.call(cbind,lapply(AP.fixed, function(x) x$Psd))

+

+    Pmax <- apply(PSummary,2,max)

+    Pneu <- sweep(PSummary,2,Pmax,FUN="/")

+    Aneu <- sweep(ASummary,1,Pmax,FUN="*")

+

+    X <- apply(Pneu,2,range)

+    Y <- apply(setPs,2,range)

+    colnames(X) <- colnames(Y)

+    if (all.equal(X,Y,tolerance=0.01) != TRUE)

+        warning("Patterns do not match fixed values.")

+

+    Ps4fixAs<-list("P"=Pneu,"Psd"=Psd)

+    return(Ps4fixAs)

+}