\name{tweeDE}
\alias{tweeDE}
\alias{testPoissonTweedie}
\alias{print.tweeDE}
\alias{MAplot}
\alias{MAplot.tweeDE}
\alias{Vplot}
\alias{Vplot.tweeDE}
\title{
Score test for differences between two Poisson-Tweedie groups
}
\description{
Carry out a score test for differences between two Poisson-Tweedie groups.
}
\usage{
tweeDE(object, group, mc.cores = 1, pair = NULL, \dots)
testPoissonTweedie(x, group, saveModel = FALSE,  \dots)
MAplot(x, \dots)
Vplot(x, \dots)
\method{print}{tweeDE}(x, n=6L, sort.by="pval", log2fc.cutoff=0, pval.adjust.cutoff=1, print=TRUE, \dots)
\method{MAplot}{tweeDE}(x, log2fc.cutoff=0, highlight=NULL, \dots)
\method{Vplot}{tweeDE}(x, log2fc.cutoff=0, pval.adjust.cutoff=1, highlight=NULL, ylab=expression(paste(-log[10], " Raw P-value")), \dots)
}

\arguments{
  \item{object}{
    a \code{data.frame} or a \code{matrix} of RNA-seq counts.
  }
  \item{group}{
    vector giving the experimental group/condition for each
    sample/library.
  }
  \item{mc.cores}{
    number of cpu cores to be used. This option is only
    available when the 'multicore' package is installed and loaded first.
    In such a case, if the default value of \code{mc.cores=1} is not changed,
    all available cores will be used.
  }
  \item{pair}{
    vector of two elements containing the representants of each of the
    two groups (default is 'NULL').
  }
  \item{n}{
    maximum number of genes printed.
  }
  \item{sort.by}{
    character string, indicating whether genes should be ranked by
    their P-value (\code{pval}), which is the default setting, or
    by absolute log2 fold-change (\code{log2fc}).
  }
  \item{log2fc.cutoff}{
    cutoff on the minimum value of the log2 fold change.
  }
  \item{pval.adjust.cutoff}{
    cutoff on the maximum adjusted P-value (FDR).
  }
  \item{print}{
    logical; it indicates whether the output should be printed on the terminal.
  }
  \item{highlight}{
    list of arguments to the \code{points()} plotting function in order to highlight
    genes in the MA or volcano plots. A component called \code{genes} is expected to
    have the identifiers of the genes to be higlighted.
  }
  \item{ylab}{
    label on the y-axis of the volcano plot set by default to -log10 of the raw
     P-value which is what this plot displays on that axis.
  }
  \item{x}{
    object returned by the function \code{tweeDE} in the case of \code{print}
    and vector of count data in the case of \code{testPoissonTweedie}.
  }
  \item{saveModel}{
    logical indicating whether the results of fitting the model should
    be saved or not (default is 'FALSE').
  }
  \item{\dots}{
    additional arguments.
  }
}
\details{
  'testPoissonTweedie' performs the test for a vector of counts.
  
  'tweeDE' performs the test for a whole 'data.frame'. The P-values are
  then corrected using the Benjamini and Hochberg method.
}
\value{
  'testPoissonTweedie' returns a list with:
  
     'mean': means for each group
     'pvalue':  p-value for the test

  'tweeDE' returns a 'data.frame' with columns

  'overallMean': overall mean counts 
  'meanA': mean counts of the first group
  'meanB': mean counts of the second group
  'log2fc': logarigthm (base 2) of the fold-change (second group vs. first group)
  'pval': p-value for the test
  'pval.adjust': adjusted p-value using Benjamini-Hochberg method
}
\references{
  M. Esnaola, P. Puig, D. Gonzalez, R. Castelo, J.R. Gonzalez.
  A flexible count data model to fit the wide diversity of expression
  profiles arising from extensively replicated RNA-seq
  experiments. Submitted.

  A.H. El-Shaarawi, R. Zhu, H. Joe (2010). Modelling species abundance
  using the Poisson-Tweedie family. Environmetrics 22, pages 152-164.
  
  P. Hougaard, M.L. Ting Lee, and G.A. Whitmore (1997). Analysis of
  overdispersed count data by mixtures of poisson variables and poisson
  processes. Biometrics 53, pages 1225-1238.
}

\seealso{
  \code{\link{normalizeCounts}}
  \code{\link{mlePoissonTweedie}}
  }

\examples{
# Generate a random matrix of counts
counts <- matrix(rPT(n = 1000, a = 0.5, mu = 10, D = 5), ncol = 40)

# Test for differences between the two groups
tweeDE(counts, group = rep(c(1,2),20))
}

\keyword{htest}