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Commit cd3ebade authored by Jerome Mariette's avatar Jerome Mariette
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......@@ -320,7 +320,7 @@ plug-in \cite{jquery}, including many features easing diagram production and
enhancing their readability. In particular, jvenn can handle up to 6 lists, is
a dynamic tool and implements both proportional and Edwards layouts. The
library has already been used and cited in two scientific publications
\cite{Bianchia2013, Aravindraja2013}. It is already embedded in different Web
\cite{Bianchia2013, Aravindraja2013}. It is already embedded in different web
applications such as nG6 \cite{Mariette2012}, RNAbrowse \cite{Mariette} and
WallProtDB \cite{SanClemente}.
......@@ -393,74 +393,86 @@ identifiers of the elements contained in the area.
\subsection*{Integration}
jvenn allows programmers having only moderate JavaScript experiences to embed
Venn diagrams in a Web page without dependency. It has been designed following the
examples of jbrowse \cite{Westesson01032013}, Cytoscape-Web \cite{Lopes2010},
and jHeatmap \cite{DeuPons2014}.
Venn diagrams in a web page without dependency. It has been designed following
the examples of jbrowse \cite{Westesson01032013}, Cytoscape-Web
\cite{Lopes2010}, and jHeatmap \cite{DeuPons2014}.
The integration documentation is included in the software package which can be
downloaded from http://bioinfo.genotoul.fr/jvenn.
\subsection*{Web application}
jvenn can also be directly used as a Web application, which is available at
jvenn can also be directly used as a web application, which is available at
http://bioinfo.genotoul.fr/jvenn/example.html (Fig.~\ref{fig::web}).
jvenn's Web application performances depend on the client browser. Using the
jvenn's web application performances depend on the client browser. Using the
current version on a standard Linux computer (one cpu, four GB of RAM), it
displays a six lists diagram of 10,000 identifiers in two seconds.
\section*{Results}
M.A. Dillies and colleagues \cite{Dillies2012} have compared seven RNA-Seq data
normalization methods and given a set of best practices to help biologists in their
data processing. In table 2, they have shown the differences between methods
pair-wise. The raw data table provided by the team contains 5,277 lines and
seven columns. The columns correspond to the different methods presented in the
'Differential expression analysis' section of the article. The data in the table
was filtered ($p < 0.05$) to produce the method specific gene name lists. Six
out of seven lists were selected for further processing ; Med was left out.
The lists were uploaded to the jvenn application and a Venn diagram was
produced. Using the layout selector the diagram was shown in Edwards Venn
format, in which all figures are accessible. This view presents all the lists
overlap between methods. Considering Fig. 2, the higher values are located in
central areas of the graph showing that the methods share large portions of gene
lists. The list of 484 genes shared by DESeq, TMM, UQ and FQ has been extracted
by clicking on the corresponding figure. Gene G002562 was sought using the
search box. It was found to be part of the five genes shared by FQ and UQ.
The jvenn statistics show that the different methods produce gene lists with
very different sizes (minimum 417 - maximum 1,249) and that most of the genes are
shared between methods : 1,069 genes out of 1,347 shared by at least four methods.
M.A. Dillies and colleagues \cite{Dillies2012} have compared seven methods for
normalization and search of differentially expressed genes in RNASeq data. This
study is designed to provide a set of best practices to help biologists with
their data processing. Table 2 of the cited article is the contingency table
of the differentially expressed genes obtained from the seven methods, where
counts in the table correspond to the intersection of two lists obtained from
two different methods. The raw data table, kindly provided by the team, contains
5,277 lines and seven columns. The columns correspond to the different methods
presented in the ``Differential expression analysis'' section of their article.
The data in the table was filtered ($p < 0.05$) to retrieve the gene name lists
corresponding to each method. As, jvenn handles only six list at most, six out
of the seven lists were selected for further processing: we left out the median
normalization method because, for one hand, this method is very similar to
several other methods (as shown in the article) and, for the other hand, we
believe that median is a poor estimate of the sequencing length, which is the
bias that normalization methods try to correct. The lists were uploaded to the
jvenn application and a Venn diagram was obtained, using an Edwards layout,
which is shown in Fig.~\ref{fig::edwards}.
The same analysis was performed with VENNTURE, the only other tool able to
generate a six list Edwards Venn diagram. First, the software package was
installed on a computer running under MS-Windows. Then, the six gene lists were loaded
in an MS-Excel spreadsheet. VENNTURE was run using the spreadsheet as input
generating a static MS-PowerPoint file containing the diagram and a MS-Excel
file with all the intersection contents. The 484 genes shared by DESeq,
TMM, UQ and FQ were found in the intersection spreadsheet. The diagram did not
allow to search for gene G002562. It was found using MS-Excel text search in the
intersection spreadsheet.
installed on a computer running under MS-Windows OS. The six gene lists were
loaded in an MS-Excel spreadsheet and VENNTURE was run using the spreadsheet as
input generating a static MS-PowerPoint file containing the diagram and a MS-Excel
file with all the intersection contents.
\section*{Discussion}
jvenn enables to compare up to six lists and updates the diagram automatically
when modifying the lists content. Compared to VENNTURE it does not need any
installation and gives access to a dynamic diagram providing simple functions to
extract gene lists and perform searches.
jvenns' statistical charts give a simple and quick overview of the sizes of the
different lists and of their overlaps. It permits to compare different Venn diagrams.
These features are not available in the VENNTURE software package.
Fig.~\ref{fig::edwards} presents all the lists overlaps. The highest values are
located in central areas of the graph, showing that the corresponding methods
share large portions of gene lists. Finally, a list of 484 genes shared by
DESeq, TMM, UQ and FQ has been extracted. Gene G002562 was sought using the
search box. It was found to be part of the five genes shared by FQ and UQ.
The jvenn statistics show that the different methods produce gene lists with
very different sizes (minimum 417 - maximum 1,249) and that most of the genes are
shared between methods: 1,069 genes out of 1,347 are common between at least
four methods.
For biologists using different techniques in their experiment or in their statistical
analysis, jvenn enables to quickly extract the shared identifiers. Being found
using different approaches these elements present a higher confidence level.
The same 484 genes shared by DESeq, TMM, UQ and FQ were found in the
intersection spreadsheet. The diagram did not allow to search for gene G002562,
which was was found using MS-Excel text search in the intersection spreadsheet
nevertheless.
\section*{Conclusion}
Thanks to its numerous features, dynamic behavior and graphical layout quality, jvenn can be
efficiently used in many cases to compare different sets of results and easily extract shared
elements. Being a simple JavaScript plug-in allows to embed it in any Web
environment.
jvenn enables to compare up to six lists and updates the diagram automatically
when modifying the lists content. Compared to VENNTURE it does not need any
local installation of a new program and it gives access to a dynamic diagram
providing simple functions to extract gene lists and perform searches.
jvenn's statistics charts give a simple and quick overview of the sizes of the
different lists and of their overlaps. It permits to compare different Venn
diagrams. These features are not available in the VENNTURE software package.
For biologists using different techniques in their experiment or in their
statistical analysis, jvenn enables to quickly extract the shared identifiers.
When comparing different methods applied to extract differentially expressed
genes, these features ease the analysis.
Thanks to its numerous features, dynamic behavior and graphical layout quality,
jvenn can be efficiently used in many cases to compare different sets of results
and easily extract shared elements. Being a simple JavaScript plug-in allows to
embed it in any web environment.
\section*{Availability and requirements}
......@@ -489,7 +501,9 @@ and CK wrote the manuscript. All authors read and approved the final manuscript.
\section*{Acknowledgements}
We would like to acknowledge all our users for providing us useful feedback on
the system and for pointing out features worth developing. We thank the
reviewers for their insightful and constructive comments.
reviewers for their insightful and constructive comments. We also thank Julie
Aubert and the French StatOmique Consortium for providing us the data used in
the ``Results'' section.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% The Bibliography %%
......@@ -537,16 +551,21 @@ reviewers for their insightful and constructive comments.
diagram as a PNG file. The middle-right switch button
panel allows to activate or dis-activate lists to access a specific
intersection count. Charts showing the list size and intersection size
repartition located underneath the diagram.}
\end{figure}
repartition located underneath the diagram.}\label{fig::features}
\end{figure}
\begin{figure}[h!]
\begin{figure}[h!]
\caption{\csentence{A six lists Edwards-Venn diagram.}
On mouse over a figure, the shape corresponding to the lists involved in
the intersection are highlighted and the other ones faded out. In
this example, the user pointed the intersection between samples SRR068049,
SRR068051 and SRR068052 which contains eight different items.}
\end{figure}
SRR068051 and SRR068052 which contains eight different
items.}\label{fig::edwards}
\end{figure}
\begin{figure}[h!]
\caption{\csentence{???.}???}\label{fig::web}
\end{figure}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% %%
......@@ -559,7 +578,8 @@ reviewers for their insightful and constructive comments.
\section*{Tables}
\begin{table}[h!]
\caption{Features of a subset of already available software packages, and jvenn.}
\caption{Features of a subset of already available software packages, and
jvenn.}\label{table::features}
\begin{tabular}{c|cccccc}
Application & Maximum & Layouts & Application &
Proportionality & Input data & Output\\
......@@ -574,10 +594,10 @@ reviewers for their insightful and constructive comments.
& R object \\
& & & & & & and TIFF \\ \hline
BioVenn \cite{Hulsen2008} & 3 & Classical & Web application & Yes &
BioVenn \cite{Hulsen2008} & 3 & Classical & web application & Yes &
Lists & SVG and PNG \\ \hline
venny \cite{venny} & 4 & Classical & Web application & No &
venny \cite{venny} & 4 & Classical & web application & No &
Lists & PNG \\ \hline
Canvasxpress \cite{canvasxpress} & 4 & Classical & JavaScript library &
......@@ -588,7 +608,7 @@ reviewers for their insightful and constructive comments.
Yes & Lists & PNG \\
Chart API \cite{googleAPI} & & & & & & \\ \hline \hline
jvenn & 6 & Classical & Web application & No & Lists,
jvenn & 6 & Classical & web application & No & Lists,
& Interactive
\\
& & and Edwards & and JavaScript & & intersection & diagram, \\
......@@ -599,7 +619,7 @@ reviewers for their insightful and constructive comments.
\begin{table}[h!]
\caption{Available formats and example for the \textit{series} option.}
\caption{Available input formats.}\label{table::format}
\begin{tabular}{cccc}
\hline
Format & Example\\ \hline
......
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