\name{sig.score}
\alias{sig.score}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Function to compute signature scores as linear combination of gene expressions
}
\description{
This function computes a signature score from a gene list (aka gene signature), i.e. a signed average as published in Sotiriou et al. 2006 and Haibe-Kains et al. 2009.
}
\usage{
sig.score(x, data, annot, do.mapping = FALSE, mapping, size = 0,
  cutoff = NA, signed = TRUE, verbose = FALSE)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
  \item{x}{
Matrix containing the gene(s) in the gene list in rows and at least three columns: "probe", "EntrezGene.ID" and "coefficient" standing for the name of the probe, the NCBI Entrez Gene id and the coefficient giving the direction and the strength of the association of each gene in the gene list.
}
  \item{data}{
Matrix of gene expressions with samples in rows and probes in columns, dimnames being properly defined.
}
  \item{annot}{
Matrix of annotations with at least one column named "EntrezGene.ID", dimnames being properly defined.
}
  \item{do.mapping}{
\code{TRUE} if the mapping through Entrez Gene ids must be performed (in case of ambiguities, the most variant probe is kept for each gene), \code{FALSE} otherwise.
}
  \item{mapping}{
Matrix with columns "EntrezGene.ID" and "probe" used to force the mapping such that the probes are not selected based on their variance.
}
  \item{size}{
Integer specifying the number of probes to be considered in  signature computation. The probes will be sorted by absolute value of coefficients.
}
  \item{cutoff}{
Only the probes with coefficient greater than \code{cutoff} will be considered in signature computation.
}
  \item{signed}{
\code{TRUE} if only the sign of the coefficient must be considered in signature computation, \code{FALSE} otherwise.
}
  \item{verbose}{
\code{TRUE} to print informative messages, \code{FALSE} otherwise.
}
}
%%\details{
%%  ~~ If necessary, more details than the description above ~~
%%}
\value{
  \item{score }{Signature score.}
  \item{mapping }{Mapping used if necessary.}
  \item{probe }{If mapping is performed, this matrix contains the correspondence between the gene list (aka signature) and gene expression data.}
}
\references{
Sotiriou C, Wirapati P, Loi S, Harris A, Bergh J, Smeds J, Farmer P, Praz V, Haibe-Kains B, Lallemand F, Buyse M, Piccart MJ and Delorenzi M (2006) "Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis", \emph{Journal of National Cancer Institute}, \bold{98}:262-272

Haibe-Kains B (2009) "Identification and Assessment of Gene Signatures in Human Breast Cancer", PhD thesis at \emph{Universite Libre de Bruxelles}, \url{http://theses.ulb.ac.be/ETD-db/collection/available/ULBetd-02182009-083101/}
}
\author{
Benjamin Haibe-Kains
}
%%\note{
%%  ~~further notes~~
%%}

%% ~Make other sections like Warning with \section{Warning }{....} ~

%%\seealso{
%% ~~objects to See Also as \code{\link{help}}, ~~~
%%}
\examples{
## load NKI data
data(nkis)
## load GGI signature
data(sig.ggi)
## make of ggi signature a gene list
ggi.gl <- cbind(sig.ggi[ ,c("probe", "EntrezGene.ID")],
  "coefficient"=ifelse(sig.ggi[ ,"grade"] == 1, -1, 1))
## computation of signature scores
ggi.score <- sig.score(x=ggi.gl, data=data.nkis, annot=annot.nkis,
  do.mapping=TRUE, signed=TRUE, verbose=TRUE)
str(ggi.score)
}
% Add one or more standard keywords, see file 'KEYWORDS' in the
% R documentation directory.
\keyword{ models }