--- a
+++ b/man/classifySamples.Rd
@@ -0,0 +1,51 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/pRRophetic.R
+\name{classifySamples}
+\alias{classifySamples}
+\title{Dichotimize a training expression set and fit a logistic ridge regression model which is applied to the test expression matirx.}
+\usage{
+classifySamples(
+  trainingExprData,
+  trainingPtype,
+  testExprData,
+  batchCorrect = "eb",
+  minNumSamples = 10,
+  selection = -1,
+  printOutput = TRUE,
+  numGenesSelected = 1000,
+  numSens = 15,
+  numRes = 55
+)
+}
+\arguments{
+\item{trainingExprData}{Gene expression matrix for samples for which we the phenotype is already known.}
+
+\item{trainingPtype}{The known phenotype, a vector in the same order as the columns of "trainingExprData" or with the same names as colnames of "trainingExprData".}
+
+\item{testExprData}{Gene expression matrix for samples on which we wish to predict a phenotype. Gene names as rows, samples names as columns.}
+
+\item{batchCorrect}{The type of batch correction to be used. Options are "eb", "none", .....}
+
+\item{minNumSamples}{The minimum number of test samples, print an error if the number of columns of "testExprData" is below this threshold. A large number of test samples may be necessary to correct for batch effects.}
+
+\item{selection}{How should duplicate gene ids be handled. Default is -1 which asks the user. 1 to summarize by their or 2 to disguard all duplicates.}
+
+\item{printOutput}{Set to FALSE to supress output}
+
+\item{numGenesSelected}{Specifies how genes are selected for "variableSelectionMethod". Options are "tTests", "pearson" and "spearman".}
+
+\item{numSens}{The number of sensitive cell lines to be fit in the logistic regression model.}
+
+\item{numRes}{The number of resistant cell lines fit in the logistic regression model.}
+}
+\value{
+classifySamples
+}
+\description{
+Dichotimize a training expression set and fit a logistic ridge regression model which is applied to the test expression matirx.
+This function will return a set of probabilities.
+}
+\author{
+Paul Geeleher, Nancy Cox, R. Stephanie Huang
+}
+\keyword{internal}