\name{exomeCopy-package}
\alias{exomeCopy-package}
\alias{exomeCopy-package}
\docType{package}
\title{
  CNV detection from exome sequencing read depth
}
\description{
  Detection of copy number variants (CNV) from exome sequencing samples,
  including unpaired samples.  The package implements a hidden Markov
  model which uses positional covariates, such as background read depth
  and GC-content, to simultaneously normalize and segment the samples
  into regions of constant copy count.  
}
\details{

  \tabular{ll}{
    Package: \tab exomeCopy\cr
    Type: \tab Package\cr
    Version: \tab 1.1.11\cr
    Date: \tab 2012-03-12\cr
    License: \tab GPL (>= 2)\cr
    LazyLoad: \tab yes\cr
    Imports: \tab BiocGenerics \cr
    Depends: \tab methods, graphics, IRanges, GenomicRanges, Rsamtools \cr
    Suggests: \tab Biostrings\cr
  }

  exomeCopy fits a hidden Markov model to observed read counts using
  covariates.  It returns the Viterbi path, the most likely path of
  hidden states, which is the predicted copy count at each window.

  \code{exomeCopy} is designed to run on read counts from consecutive
  genomic ranges on a single chromosome, as it tries to identify higher
  or lower read depth relative to a baseline.  Please see the vignette
  for an example of how to prepare input data for \code{exomeCopy}, how
  to loop the function over multiple chromosomes and samples, and how to
  extract the resulting predicted CNVs.  
}
\author{
  Michael Love <love@molgen.mpg.de>
}
\references{
  Love, Michael I.; Mysickova, Alena; Sun, Ruping; Kalscheuer, Vera;
  Vingron, Martin; and Haas, Stefan A. (2011) "Modeling Read Counts for
  CNV Detection in Exome Sequencing Data," Statistical Applications in
  Genetics and Molecular Biology: Vol. 10 : Iss. 1, Article 52. DOI: 10.2202/1544-6115.1732
  \url{http://cmb.molgen.mpg.de/publications/Love_2011_exomeCopy.pdf}.
}
\keyword{ package }
\seealso{
  \code{\link{exomeCopy}}
}