5.21 KB
Newer Older
#+TITLE: Vidjil -- High-throughput Analysis of V(D)J Immune Repertoire
#+AUTHOR: The Vidjil team (Mathieu, Mikaël, Aurélien, Florian, Marc, Ryan and Tatiana)

Mathieu Giraud's avatar
Mathieu Giraud committed
6 7

# Vidjil -- V(D)J recombinations analysis -- [[]]
# Copyright (C) 2011-2017 by Bonsai bioinformatics at CRIStAL (UMR CNRS 9189, Université Lille) and Inria Lille
11 12 13 14 15 16 17 18 19
# [[]]

V(D)J recombinations in lymphocytes are essential for immunological
diversity. They are also useful markers of pathologies, and in
leukemia, are used to quantify the minimal residual disease during
patient follow-up.
High-throughput sequencing (NGS/HTS) now enables the deep sequencing 
of a lymphoid population with dedicated [[][Rep-Seq]] methods and softwares.

20 21
The Vidjil platform contains three components. The Vidjil algorithm
process high-througput sequencing data to *extract V(D)J
22 23 24
junctions and gather them into clones*. Vidjil starts 
from a set of reads and detects "windows" overlapping the actual CDR3.
This is based on an fast and reliable seed-based heuristic and allows
25 26 27
to output all sequenced clones. The analysis is extremely fast
because, in the first phase, no alignment is performed with database
germline sequences. 

The Vidjil *web application* is made for the interactive visualization and
analysis of clones and their tracking along the time in a MRD setup or
31 32 33
in a immunological study. The web application can visualize data processed by
the Vidjil algorithm or by other V(D)J analysis pipelines, and
enables to explore further cluterings proposed
by software and/or done manually done by the user.
35 36 37 38 39
The web application can be linked to a *sample, experiment and patient database*
able to store sequencing data and metadata, to run RepSeq software
and to save annotations directly from the web application, with authentication.
Clinicians or researchers in immunology or hematology
can manage, upload, analyze and annotate their runs directly on the web applicaiton.
40 41 42 43 44

* Vidjil components

** The algorithm

- Stable releases can be downloaded from
- Development code is under [[algo/]]
- Documentation, compilation and installation instructions: [[doc/]]

** The web application

- Access at (demo login:, password: vidjil)
- Please contact us if you would like to test your data and have a full account on the web server
53 54
- Development code is under [[browser/]] and [[server/]] (a =make= in those directories
  will get the necessary files)
- Documentation is in [[doc/]], it is also available from [[]]
56 57 58 59

* Code and license

Vidjil is open-source, released under GNU GPLv3 license. 
Mathieu Giraud's avatar
Mathieu Giraud committed
60 61 62 63
You are welcome to redistribute it under [[][certain conditions]]. 
This software is for research use only and comes with no warranty.

The development code is available on [[]].
64 65 66 67
Bug reports, issues and patches are welcome.

* The Vidjil team

Mathieu Giraud's avatar
Mathieu Giraud committed
Vidjil is developed by Aurélien Béliard, [[][Mathieu Giraud]], Ryan Herbert, Tatiana Rocher and [[][Mikaël Salson]]
from the [[][Bonsai bioinformatics team]] (CRIStAL, CNRS, U. Lille, Inria Lille).
Mikaël Salson's avatar
Mikaël Salson committed
70 71
Vidjil is also developed by external colleagues:
Marc Duez located in Bristol (School of Social and Community Medicine, University of Bristol)
Mathieu Giraud's avatar
Mathieu Giraud committed
and Florian Thonier located in Rennes (department of hematology)
73 74 75 76
Vidjil is developed in collaboration with 
the [[][department of Hematology]] of CHRU Lille, 
the [[][Functional and Structural Genomic Platform]] (U. Lille 2, IFR-114, IRCL), 
and the [[][EuroClonality-NGS]] working group.
Mathieu Giraud's avatar
Mathieu Giraud committed
77 78
The research is supported by SIRIC ONCOLille (Grant INCa-DGOS-Inserm 6041), by Région Nord-Pas-de-Calais/Hauts-de-France (ABILES),
by Inria and by InCA.

Mikaël Salson's avatar
Mikaël Salson committed
* References

82 83 84
If you use Vidjil for your research, please cite the following references:

Marc Duez et al.,
“Vidjil: A web platform for analysis of high-throughput repertoire sequencing”,
86 87
PLOS ONE 2016, 11(11):e0166126
88 89 90 91 92 93

Mathieu Giraud, Mikaël Salson, et al.,
“Fast multiclonal clusterization of V(D)J recombinations from high-throughput sequencing”,
BMC Genomics 2014, 15:409 

Mikaël Salson's avatar
Mikaël Salson committed
94 95 96 97 98 99 100
You may also be interested in the following publication for the diagnosis of
acute lymphoblastic leukemia with high-throughput sequencing:

Yann Ferret, Aurélie Caillault, et al., “Multi-loci diagnosis of acute
lymphoblastic leukaemia with high-throughput sequencing and bioinformatics
analysis”, British Journal of Haematology 2016