Rough outline of the Melanoma analysis presentation.

lectures/melanoma/Makefile

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lectures/melanoma/assemblyline.jpg

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lectures/melanoma/beamerthemelumc.sty

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lectures/melanoma/logos

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lectures/melanoma/melanoma.tex

+\documentclass[slidestop]{beamer}
+
+\author{Jeroen F.J. Laros}
+\title{Whole genome sequencing in Dutch melanoma families}
+\providecommand{\mySubTitle}{Experiences and challenges}
+\providecommand{\myConference}{MTG work discussion}
+\providecommand{\myDate}{3-dec-2015}
+\providecommand{\myGroup}{Leiden Genome Technology Center}
+\providecommand{\myDepartment}{Department of Human Genetics}
+\providecommand{\myCenter}{Center for Human and Clinical Genetics}
+
+\usetheme{lumc}
+
+\begin{document}
+
+% This disables the \pause command, handy in the editing phase.
+%\renewcommand{\pause}{}
+
+% Make the title slide.
+\makeTitleSlide{}
+
+% First page of the presentation.
+\section{Introduction}
+\subsection{Samples}
+\begin{pframe}
+  X families, about Y members per family.
+  \begin{itemize}
+    \item Full genome.
+    \item $z\times$ coverage.
+  \end{itemize}
+\end{pframe}
+
+\section{Data generation}
+\subsection{Sequencing}
+\begin{pframe}
+  \begin{minipage}[t]{0.47\textwidth}
+    \begin{figure}
+      \includegraphics[width=\textwidth]{hiseq_2000}
+      \caption{HiSeq 2500.}
+    \end{figure}
+  \end{minipage}
+  \hfill
+  \begin{minipage}[t]{0.47\textwidth}
+    Characteristics:
+    \begin{itemize}
+      \item High throughput.
+      \item Paired end.
+      \item High accuracy.
+      \item Read length $2 \times 150$bp.
+      \item Run time of 6 days.
+    \end{itemize}
+  \end{minipage}
+\end{pframe}
+
+\begin{pframe}
+  Sequencing was one at the Sanger institute.
+  % 938528037 mapped reads
+  % 1672174 unmapped reads
+
+  \begin{itemize}
+    \item Two times $100$ nucleotides.
+    \item $1,\!000,\!000,\!000$ reads.
+    \item $100,\!000,\!000,\!000$ nucleotides.
+    \item $150$GB of data per sample (compressed).
+  \end{itemize}
+  \bigskip
+
+  A grand total of $4.5$TB was used, which completely filled up the storage at
+  Sanger.
+
+  \vfill
+  \permfoot{\url{http://www.sanger.ac.uk/}}
+\end{pframe}
+
+\subsection{Data transfer}
+\begin{pframe}
+  We need to make sure the data is transfered in a \emph{secure} way.
+
+  Sending disks?
+
+  Public server, GPG encryption.
+\end{pframe}
+
+
+\subsection{Pipelines}
+\begin{pframe}
+  \begin{figure}[]
+    \vspace{-0.5cm}
+    \begin{center}
+      \includegraphics[height=0.75\textheight]{assemblyline}
+    \end{center}
+    \caption{Scene from ``Modern times''.}
+  \end{figure}
+\end{pframe}
+
+\subsection{Data analysis}
+\begin{pframe}
+  Resequencing pipelines can roughly be divided in five steps.
+  \begin{enumerate}
+    \item Pre-alignment.
+    \begin{itemize}
+      \item Quality control.
+      \item Data cleaning.
+    \end{itemize}
+    \item Alignment.
+    \begin{itemize}
+      \item Post-alignment quality control.
+    \end{itemize}
+    \item Variant calling.
+    \item Filtering.
+    \begin{itemize}
+      \item Post-variant calling quality control.
+    \end{itemize}
+    \item Annotation.
+  \end{enumerate}
+\end{pframe}
+
+\begin{frame}
+  \frametitle{Principle of variant calling}
+
+  \begin{figure}[]
+    \begin{center}
+      \includegraphics[width=0.9\textwidth]{varcall}
+    \end{center}
+    \caption{Result of an alignment.}
+    \label{}
+  \end{figure}
+\end{frame}
+
+\subsection{Prioritisation}
+\begin{pframe}
+  Prioritisation is mainly done by filtering variants that we expect to be
+  irrelevant.
+  \bigskip
+  \pause
+
+  This can be because the variant does not follow the \emph{inheritance
+  pattern} of the disease.
+  \begin{itemize}
+    \item The disease is recessive, but the variant is \emph{homozygous} in an
+      unaffected individual.
+  \end{itemize}
+  \bigskip
+  \pause
+
+  It can be because the \emph{predicted effect} of a variant does not fit in
+  the phenotype.
+  \begin{itemize}
+    \item A variant found in an unrelated gene.
+    \item A variant that does not alter the protein.
+  \end{itemize}
+\end{pframe}
+
+\section{Annotation}
+\subsection{Effect prediction}
+\begin{pframe}
+  In most cases we are still left with a lot of variants.
+  \bigskip
+
+  Variant annotation.
+  \begin{itemize}
+    \item Frequency within a population.
+    \item Location of the variant.
+    \begin{itemize}
+      \item Gene panels.
+      \item Location within a gene.
+    \end{itemize}
+    \item Conservation.
+  \end{itemize}
+\end{pframe}
+
+\subsection{Variant Effect Predictor}
+\begin{pframe}
+  A selection of VEP annotation:
+  \begin{itemize}
+    \item Affected genes and transcripts.
+    \item Location of the variant.
+    \begin{itemize}
+      \item Upstream of a transcript, in coding sequence, in non-coding RNA,
+        in regulatory region.
+    \end{itemize}
+    \item Consequence on the protein sequence.
+    \begin{itemize}
+      \item Stop gained, missense, stop lost, frameshift.
+    \end{itemize}
+    \item Minor allele frequencies from the 1000 Genomes Project.
+    \item SIFT and PolyPhen scores for changes to protein sequence.
+  \end{itemize}
+
+  \vfill
+  \permfoot{\url{http://www.ensembl.org/info/docs/tools/vep/index.html}}
+\end{pframe}
+
+\subsection{Databases}
+\begin{pframe}
+  In most cases we are not interested in common variants.
+  \begin{itemize}
+    \item dbSNP.
+    \item 1000 Genomes.
+    \item Exome Variant Server (EVS).
+  \end{itemize}
+  \medskip
+
+  A cut-off of $1\%$ is usually fine.
+  \bigskip
+  \pause
+
+  Databases containing detailed information about variants:
+  \begin{itemize}
+    \item \emph{Locus specific} databases.
+    \begin{itemize}
+      \item LOVD.
+    \end{itemize}
+    \item Human Gene Mutation Database (HGMD).
+  \end{itemize}
+
+  \vfill
+  \bs{\url{http://www.lovd.nl/}}
+
+  \bs{\url{http://www.hgmd.cf.ac.uk/}}
+\end{pframe}
+
+\begin{pframe}
+  % iets moet in alle familieleden voorkomen, maar mag niet in een deel van een
+  % andere familie voorkomen maar wel in de gehele familie
+
+  \begin{table}[]
+    \begin{center}
+      \begin{tabular}{ccl}
+        Family one & Family two & Filter result \\
+        \hline
+        $5/5$      & $4/4$      & Passed \\
+        $0/5$      & $4/4$      & Passed \\
+        $3/5$      & $4/4$      & Filtered \\
+        $3/5$      & $3/4$      & Filtered \\
+      \end{tabular}
+    \end{center}
+    \caption{The advanced intersection.}
+  \end{table}
+\end{pframe}
+
+\begin{pframe}
+  \begin{table}[]
+    \begin{center}
+      \begin{tabular}{lr}
+        Filter                & Variants left \\
+        \hline
+        None                  & $12,\!820,\!660$ \\
+        Unaffected member     &  $7,\!354,\!674$ \\
+        EU MAF below $1$\%    &  $5,\!504,\!165$ \\
+        GoNL MAF below $1$\%  &  $4,\!681,\!268$ \\
+        Intersection          &  $5,\!973,\!169$ \\
+        Advanced intersection &  $1,\!549,\!550$
+      \end{tabular}
+    \end{center}
+    \caption{Single filters.}
+  \end{table}
+\end{pframe}
+
+\begin{pframe}
+  \begin{table}[]
+    \begin{center}
+      \begin{tabular}{lr}
+        Filter                & Variants left \\
+        \hline
+        None                  & $12,\!820,\!660$ \\
+        EU MAF below $1$\%    &  $5,\!504,\!165$ \\
+        GoNL MAF below $1$\%  &  $4,\!327,\!913$ \\
+        Unaffected member     &  $2,\!471,\!569$ \\
+        Intersection          &      $479,\!494$ \\
+        Advanced intersection &       $40,\!944$
+      \end{tabular}
+    \end{center}
+    \caption{Combining filters.}
+  \end{table}
+
+(25.127 in all families)
+\end{pframe}
+
+\subsection{Conservation}
+\begin{pframe}
+  \begin{figure}[]
+    \begin{center}
+      \includegraphics[width=\textwidth]{phylop}
+    \end{center}
+    \caption{PhyloP scores based on $100$ vertebrate species.}
+  \end{figure}
+
+  \vfill
+  \permfoot{\url{http://compgen.bscb.cornell.edu/phast/}}
+
+  \permfoot{\phantom{.}}
+\end{pframe}
+
+% Make the acknowledgements slide.
+\makeAcknowledgementsSlide{
+  \begin{tabular}{lll}
+    \bf Dermatology      & \bf SASC             & \bf Sanger \\
+    Mijke Visser         & Peter van 't Hof     & Thomas Keane \\
+    Nelleke Gruis        & Sander van der Zeeuw & Kim Wong \\
+    Nienke van der Stoep & Leon Mei             & Daniela Espinoza \\
+    Remco van Doorn      &                      & David Adams \\
+  \end{tabular}
+}
+
+\end{document}

lectures/melanoma/phylop.xcf

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lectures/melanoma/varcall.gif

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presentation @ 63b5792d

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+Subproject commit 63b5792d877b40e3ffeca84ece106e63159439cb