Commit b262a22b authored by Mathieu Giraud's avatar Mathieu Giraud

tutorial: encore split

parent d842c0e5
......@@ -38,36 +38,7 @@ In the following sections, we focus on the diagnosis sample.
% how to view and filter clones and
The section~\ref{sec:tracking} will deal with the comparison of several samples.
\section{Assessing the quality of the run and of the analysis}
The Vidjil web application allows to run several ``RepSeq'' (immune repertoire analysis) algorithms.
Each RepSeq algorithm has its own definition of what a clone is (or, more precisely
a clonotype), how to output its sequence and how to assign a V(D)J designation.
The number of analyzed reads will depend on the algorithm used.
This sample has been processed using the Vidjil algorithm.
\marginpar{The percentage of analyzed reads can range from .01\,\% (for
RNA-Seq or capture data) to 98-99\,\% (for very high-quality runs mostly on
\question{How many reads have been analyzed in the current sample with the embedded algorithm ?}
Now we will try to assess the reason why some reads were not analyzed in our
This might reflect a problem during the sequencing protocol\dots or that could
be normal.
For that sake you will need to display the information box by clicking on the
\textit{i} in the upper left part.
\question{What are the average read lengths on IGH? and on TRG?}
The lines starting with \texttt{UNSEG} display the reasons why some reads have
not been analyzed.
You can see what those reasons mean in the online documentation of the
algorithm: \href{\#unsegmentation-causes}{\#unsegmentation-causes
\question{What are the major causes explaining the reads have not been
analyzed? Also have a look at the average read lengths of these causes. Do
you notice something regarding the average read lengths?}
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