consensusSubtypingCOCA

apply consensus clustering give several clustering solutions

consensusSubtypingCOCA(
  dataToClust,
  targetk,
  cocanames,
  newclustername,
  reorderingVariable,
  idvar,
  visitName,
  baselineVisit,
  maxK,
  consensusmethod = "kmeans",
  returnonehot = FALSE,
  binnmf = 0,
  verbose = TRUE
)

Arguments

dataToClust

dataframe input that contains the relevant variables (may have others as well)

targetk

the desired number of classes

cocanames

names of columns to use for the consensus

newclustername

the column name for the consensus clustering

reorderingVariable

the name of the column to use to reorder the cluster names

idvar

variable name for unique subject identifier column

visitName

the column name defining the visit variables

baselineVisit

the string naming the baseline visit

maxK

maximum number of clusters

consensusmethod

either kmeans or hclust

returnonehot

boolean

binnmf

integer (0 is default - no nmf)

verbose

boolean

Value

new dataframe with new variables attached

Author

Avants BB

Examples

mydf = generateSubtyperData( 100 )