From 79db5c8fcc10f9152d3fc5923a6cf3fc15e60c36 Mon Sep 17 00:00:00 2001
From: "J.F.J. Laros" <j.f.j.laros@lumc.nl>
Date: Wed, 21 May 2014 17:20:03 +0200
Subject: [PATCH] Added introduction lecture (extracted from extended
introduction).
---
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--- a/introduction_extended/introduction_extended.tex
+++ b/introduction/introduction.tex
@@ -1,7 +1,7 @@
\documentclass[slidestop]{beamer}
\title{Introduction to NGS data analysis}
-\providecommand{\myConference}{Workshop NGS, Hogeschool Leiden}
+\providecommand{\myConference}{Introduction NGS Data Analysis}
\providecommand{\myDate}{Thursday, May 22, 2014}
\author{Jeroen F. J. Laros}
\providecommand{\myGroup}{Leiden Genome Technology Center}
@@ -340,93 +340,7 @@
\end{itemize}
\end{pframe}
-\section{Resequencing}
-\subsection{Data analysis}
-\begin{pframe}
- Resequencing pipelines can roughly be divided in five steps.
- \pause
- \begin{enumerate}
- \item Pre-alignment.
- \begin{itemize}
- \item Quality control.
- \item Data cleaning.
- \end{itemize}
- \pause
- \item Alignment.
- \begin{itemize}
- \item Post-alignment quality control.
- \end{itemize}
- \pause
- \item Variant calling.
- \pause
- \item Filtering.
- \begin{itemize}
- \item Post-variant calling quality control.
- \end{itemize}
- \pause
- \item Annotation.
- \end{enumerate}
-\end{pframe}
-
-\section{Pre-alignment}
-\subsection{Data cleaning}
-\begin{pframe}
- Depending on the sequencing platform, parts of the reads need to be removed.
- \begin{itemize}
- \item Remove linker sequences (\emph{Cutadapt}, \emph{FASTX toolkit}).
- \item Clip low quality reads at the end of the read (\emph{Sickle},
- \emph{Trimmomatic}, \emph{FASTX toolkit}).
- \item Length filtering (\emph{Fastools}).
- \end{itemize}
-
- \vfill
- \permfoot{http://code.google.com/p/cutadapt/}
-
- \permfoot{http://hannonlab.cshl.edu/fastx\_toolkit/}
-
- \permfoot{https://github.com/najoshi/sickle}
-
- \permfoot{http://www.usadellab.org/cms/index.php?page=trimmomatic}
-
- \permfoot{https://pypi.python.org/pypi/fastools}
-\end{pframe}
-
-\subsection{Trimming}
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[height=0.85\textheight]{pretrimmed_qscores}
- \end{center}
- \caption{Quality score per position.}
- \end{figure}
-\end{pframe}
-
-\subsection{Clipping}
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[height=0.85\textheight]{linker-clip}
- \end{center}
- \caption{Sequencing linkers.}
- \end{figure}
-\end{pframe}
-
\subsection{Quality control}
-\begin{pframe}
- The \emph{FastQC toolkit} can be used for quality control (both before and
- after the data cleaning step).
- \begin{itemize}
- \item GC content.
- \item GC distribution.
- \item Quality scores distribution.
- \item \ldots
- \end{itemize}
-
- \vfill
- \permfoot{http://www.bioinformatics.babraham.ac.uk/projects/fastqc/}
-\end{pframe}
-
-\subsection{Example QC output}
\begin{pframe}
\begin{figure}
\includegraphics[width=\textwidth, height=0.35\textheight]
@@ -464,55 +378,6 @@
\end{minipage}
\end{pframe}
-\subsection{Choose an aligner}
-\begin{pframe}
- Not all aligners can deal with indels.
- \begin{itemize}
- \item Only a couple of years ago, only SNPs were considered.
- \begin{itemize}
- \item \emph{Bowtie}.
- \end{itemize}
- \end{itemize}
- \medskip
- \pause
-
- Few aligners can work with large deletions.
- \begin{itemize}
- \item Spliced RNA.
- \begin{itemize}
- \item \emph{GMAP} / \emph{GSNAP}.
- \item \emph{Tophat}.
- \end{itemize}
- \item \emph{BWA-MEM}.
- \end{itemize}
-
- \vfill
- \permfoot{http://bowtie-bio.sourceforge.net/index.shtml}
-
- \permfoot{http://research-pub.gene.com/gmap/}
-
- \permfoot{http://tophat.cbcb.umd.edu/}
-
- \permfoot{http://bio-bwa.sourceforge.net/}
-\end{pframe}
-
-\begin{pframe}
- The choice of aligner may be restricted by the sequencer.
- \begin{itemize}
- \item For the Ion Torrent: \emph{Tmap}.
- \begin{itemize}
- \item Combination of three different aligners.
- \item Deals with errors in homopolymer stretches.
- \end{itemize}
- \item For the PacBio: \emph{BLASR}.
- \end{itemize}
-
- \vfill
- \permfoot{https://github.com/iontorrent/TS/tree/master/Analysis/TMAP}
-
- \permfoot{https://github.com/PacificBiosciences/blasr}
-\end{pframe}
-
\section{Variant calling}
\subsection{Consistent deviations from the reference}
\begin{pframe}
@@ -524,181 +389,8 @@
\end{figure}
\end{pframe}
-\subsection{Some considerations}
-\begin{pframe}
- Things a variant caller might take into account:
- \begin{itemize}
- \item Strand balance.
- \item Base quality.
- \item Mapping quality.
- \begin{itemize}
- \item Distribution within the reads.
- \end{itemize}
- \item Ploidity of the organism in question.
- \end{itemize}
- \medskip
- \pause
-
- Complicating factors:
- \begin{itemize}
- \item Pooled samples.
- \pause
- \item RNA.
- \begin{itemize}
- \item Allele specific expression.
- \item RNA editing.
- \end{itemize}
- \pause
- \item Strand specific sampleprep.
- \end{itemize}
-\end{pframe}
-
-\subsection{Choice of variant caller}
-\begin{pframe}
- Rules of thumb:
- \begin{itemize}
- \item Well known organism and experiment: Statistical model.
- \item Use a simpler variant caller otherwise.
- \end{itemize}
- \bigskip
- \pause
-
- Popular variant callers:
- \begin{itemize}
- \item \emph{Samtools}.
- \item \emph{GATK}.
- \item \emph{VarScan}.
- \end{itemize}
-
- \vfill
- \permfoot{http://samtools.sourceforge.net/}
-
- \permfoot{https://www.broadinstitute.org/gatk/}
-
- \permfoot{http://varscan.sourceforge.net/}
-\end{pframe}
-
-\section{Variant filtering}
-\subsection{Filtering on coverage}
-\begin{pframe}
- We can set some thresholds:
- \begin{itemize}
- \item Minimum.
- \item Maximum.
- \end{itemize}
- \bigskip
- \pause
-
- We filter for a maximum coverage because of copy number variation.
- \bigskip
- \pause
-
- A good way to calculate the maximum:
- \begin{itemize}
- \item Calculate the mean coverage.
- \begin{itemize}
- \item Only of the covered (targeted) regions.
- \end{itemize}
- \item Multiply this number with a reasonable factor e.g., $2.5$.
- \end{itemize}
-\end{pframe}
-
-\section{Annotation}
-\subsection{What is already known about a variant}
-\begin{pframe}
- A selection of SeattleSeq annotation:
- \begin{itemize}
- \item Is the variant known?
- \item Does it hit a gene?
- \pause
- \begin{itemize}
- \item Is it in an intron?
- \begin{itemize}
- \item Does it hit a splice site?
- \end{itemize}
- \pause
- \item Is it in the coding region?
- \begin{itemize}
- \item Is there a gain/loss of a stop codon?
- \item Does the variant result in a frameshift?
- \item \ldots
- \end{itemize}
- \pause
- \item Is it in the 5'/3' UTR of a gene?
- \item \ldots
- \end{itemize}
- \pause
- \item Is it in a regulatory region?
- \item \ldots
- \end{itemize}
-\end{pframe}
-
-\section{Full genome sequencing}
-\subsection{Copy number variation}
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[trim=0 5cm 0 0, clip, height=0.9\textheight, width=\textwidth]{cnv}
- \end{center}
- \caption{Coverage patterns over a whole chromosome.}
- \end{figure}
-\end{pframe}
-
-\begin{pframe}
- Per sample:
- \begin{itemize}
- \item The reference needs to be very good.
- \item Sequencability biases.
- \item Mapping biases.
- \end{itemize}
- \bigskip
- \pause
-
- Within a population:
- \begin{itemize}
- \item Mixture of distributions.
- \item Not sensitive to aforementioned biases.
- \item Needs a lot of controls.
- \end{itemize}
-\end{pframe}
-
-\subsection{Structural variation}
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[height=0.9\textheight, width=\textwidth]{poorly_mapped}
- \end{center}
- \caption{Multiple issues while mapping.}
- \end{figure}
-\end{pframe}
-
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[trim=0 19cm 0 0, clip, width=\textwidth]{discordant}
- \end{center}
- \caption{Discordant and split reads.}
- \end{figure}
-
- \vfill
- \permfoot{http://breakdancer.sourceforge.net/}
-
- \permfoot{http://sourceforge.net/projects/pindel/}
-\end{pframe}
-
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[height=0.9\textheight]{sv}
- \end{center}
- \caption{Different types of structural variation.}
- \end{figure}
-\end{pframe}
-
-
\section{De Novo assembly}
\subsection{Assesmbly}
-
\begin{pframe}
\begin{figure}[]
\begin{center}
@@ -708,35 +400,6 @@
\end{figure}
\end{pframe}
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[width=\textwidth]{contig}
- \end{center}
- \caption{Overlaps are used to reconstruct a genome.}
- \end{figure}
-\end{pframe}
-
-\subsection{Scaffolding}
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[height=0.9\textheight]{scaffold}
- \end{center}
- \caption{Paired end or mate pair reads can be used.}
- \end{figure}
-\end{pframe}
-
-\subsection{Easier assembly with PacBio}
-\begin{pframe}
- \begin{figure}[]
- \begin{center}
- \includegraphics[height=0.9\textheight]{hgap}
- \end{center}
- \caption{Correcting PacBio reads.}
- \end{figure}
-\end{pframe}
-
\section{Pipelines}
\subsection{Pipelines}
\begin{pframe}
@@ -797,42 +460,6 @@
\end{lstlisting}
\end{pframe}
-\section{Graphical interfaces}
-\subsection{Galaxy}
-\begin{pframe}
- Galaxy: a graphical user interface:
- \begin{itemize}
- \item Wrapper for command line utilities.
- \item User friendly.
- \item Point and click.
- \pause
- \item Workflows.
- \begin{itemize}
- \item Save all the steps you did in your analysis.
- \item Rerun the entire analysis on a new dataset.
- \item Share your workflow with other people.
- \item \ldots
- \end{itemize}
- \end{itemize}
-
- \vfill
- \permfoot{http://galaxy.psu.edu/}
-\end{pframe}
-
-\begin{pframe}
- \begin{figure}
- \includegraphics[trim=0 0 0 2cm, clip, width=\textwidth]{galaxy}
- \caption{Galaxy main user interface}
- \end{figure}
-\end{pframe}
-
-\begin{pframe}
- \begin{figure}
- \includegraphics[width=\textwidth, height=0.9\textheight]{galaxy_mpileup}
- \caption{User friendly interface with Galaxy}
- \end{figure}
-\end{pframe}
-
\subsection{Workflow of a parallel pipeline}
\begin{pframe}
\begin{figure}
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