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#' printClustersFromLabels
#'
#' printClustersFromLabels is function that reports that clustering results in text mode.
#'@param obj is an object of ipADMIXTURE class.
#'@param labels is a vector of labels of all individuals.
#'
#'@examples
#' h27pop_obj<-ipADMIXTURE(Qmat=ipADMIXTURE::human27pop_Qmat[[11]], admixRatioThs =0.15)
#' ipADMIXTURE::printClustersFromLabels(h27pop_obj,ipADMIXTURE::human27pop_labels)
#'
#'@export
#'
printClustersFromLabels<-function(obj,labels)
{
N<-dim(obj$Qmat)[1]
clsIDVec<-sort(unique(obj$indexClsVec) )
if(missing(labels))
{
IDs<-1:N
for(cls in clsIDVec)
{
print("===============")
M<-sum(obj$indexClsVec == cls)
print(sprintf("ID%d, md%.2f, N%d",cls,obj$homoClusters[[cls]]$maxDiffAdmixRatio,M))
print(IDs[obj$indexClsVec == cls])
}
}else{
print("Overall labels")
print("===============")
str<-""
allLabelVec<-unique(labels)
countVec<-c()
for(label_itr in allLabelVec)
{
c1<-sum( labels == label_itr )
countVec<-c(countVec,c1)
str<-sprintf("%s%s(%d)",str,label_itr,c1)
}
print(str)
for(cls in clsIDVec)
{
print("===============")
currLabels<-labels[obj$indexClsVec == cls]
currLabelsMembers<-unique(currLabels)
print(sprintf("ID%d, md%.2f, N%d",cls,obj$homoClusters[[cls]]$maxDiffAdmixRatio,length(currLabels)))
str<-""
for(label_itr in currLabelsMembers)
{
c1<-sum( currLabels == label_itr )
c2<-countVec[allLabelVec == label_itr]
str<-sprintf("%s%s(%d/%d)",str,label_itr,c1,c2)
}
print(str)
}
}
}
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