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\documentclass[a4paper]{article}

\usepackage{Bioconductor}
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\title{\emph{useR2013!}: High-throughput sequence analysis with \R{}
  and \Bioconductor{}}
\author{
  Marc Carlson \& Martin Morgan
  (\href{mailto:mtmorgan@fhcrc.org}{mtmorgan@fhcrc.org}), with
  Valerie Obenchain, Herv\'e Pag\`es, Paul Shannon, Dan Tenenbuam
}

\date{July 2013}




\usepackage{Sweave}
\begin{document}

\maketitle

\begin{abstract}

  DNA sequence analysis generates large volumes of data presenting
  challenging bioinformatic and statistical problems. This tutorial
  introduces \href{http://bioconductor.org}{\Bioconductor} packages
  and work flows for the analysis of sequence data. We learn about
  approaches for efficiently manipulating sequences and alignments,
  and introduce common work flows and the unique statistical
  challenges associated with `RNA-seq', `ChIP-seq` and variant
  annotation experiments. The emphasis is on exploratory analysis, and
  the analysis of designed experiments. The workshop assumes an
  intermediate level of familiarity with R, and basic understanding of
  biological and technological aspects of high-throughput sequence
  analysis. The workshop emphasizes orientation within the
  \Bioconductor{} milieu; we will touch on the \Biocpkg{Biostrings},
  \Biocpkg{ShortRead}, \Biocpkg{GenomicRanges}, \Biocpkg{edgeR}, and
  \Biocpkg{DiffBind}, and \Biocpkg{VariantAnnotation} packages, with
  short exercises to illustrate the functionality of each
  package. Participants should come prepared with a modern laptop with
  current \software{R} installed.

\end{abstract}

\tableofcontents

\include{chpt/Introduction}          % 1

\include{chpt/SequencesAndRanges}    % 2

\include{chpt/ReadsAndAlignments}    % 3

\include{chpt/RNASeq}                % 4

\include{chpt/ChIPSeq}               % 5

\include{chpt/Annotation}            % 6

\appendix

\bibliographystyle{abbrv}
\bibliography{References}

\end{document}
