The Vidjil algorithm processes high-througput sequencing data to extract V(D)J junctions and gather them into clones. Vidjil starts from a set of reads and detects “windows” overlapping the actual CDR3. It detects gene rearrangements from both immunoglobulins and T-cell receptors, as well as some incomplete rearrangements. The analysis is based on a reliable seed-based algorithm. It is extremely fast because, in the first phase, no alignment is performed with database germline sequences. The algorithm works on reads coming from either amplicon-based or capture-based deep sequencing strategy, as soon as they include CDR3 sequences. Both human and mouse immune systems can be analyzed.
The Vidjil web application is made for the visualization, inspection and analysis of clones and their tracking along the time in a MRD setup or in a immunological study. The application can visualize data processed by the Vidjil algorithm or by other V(D)J analysis pipelines. It enables to explore further clusterings proposed by the software and/or done manually done by the user.
The web application can be linked to a patient and sample database. With authentication, the clinicians are able to upload .fasta/.fastq/.gz file, manage and process their runs directly from the web application. They can save their analysis and generate reports for the patient record. The server with the patient database can be installed in any hospital or computer centre. A public test server is also available.
Strong attention to users and stability. High-quality development process, with systemating testing and continous integration.
All the code of Vidjil is available under open-source licenses (GPLv3, as well as some other free licences for some third-parties librairies). We also offer extended support as well as custom development for various types of projects. Please contact us if you are interested.
Vidjil is developed by a passionate team with fast response, from the Bonsai bioinformatics team of the CRIStAL (CNRS, U. Lille) and Inria Lille research centers, in Lille, France. This work is 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, and is supported by SIRIC ONCOLille (Grant INCa-DGOS-Inserm 6041), Région Nord-Pas-de-Calais (ABILES), Université Lille 1 (PPF Bioinformatique), and Inria Lille. The methods were presented at the JOBIM 2013 and ASH 2014 conferences, and are described in the following paper: