Credits

Vidjil is an open-source platform for the analysis of high-throughput sequencing data from lymphocytes, developed and maintained by the Bonsai bioinformatics lab at CRIStAL (UMR CNRS 9189, Université Lille) and Inria Lille and the VidjilNet consortium at Fondation Inria.

Contact: Mathieu Giraud and Mikaël Salson

Vidjil core development

Other contributors

.should-vdj.fa tests with curated V(D)J designations

Acknowledgements

We thank all our users, collaborators and colleagues who provided feedback on Vidjil and proposed new ideas. Our special thanks go to:

Vidjil is developed in collaboration or in connection with the following groups:

Funding

The development of Vidjil is funded by:

References

If you use vidjil-algo, please cite [Giraud, Salson 2014]. If you use the web platform, please cite [Duez 2016].

Marc Duez et al., Vidjil: A web platform for analysis of high-throughput repertoire sequencing, PLOS ONE 2016, 11(11):e0166126 http://dx.doi.org/10.1371/journal.pone.0166126

Mathieu Giraud, Mikaël Salson, et al., Fast multiclonal clusterization of V(D)J recombinations from high-throughput sequencing, BMC Genomics 2014, 15:409 http://dx.doi.org/10.1186/1471-2164-15-409

Some publications using Vidjil

Jean-Sebastien Allain et al., IGHV segment utilization in immunoglobulin gene rearrangement differentiates patients with anti-myelin-associated glycoprotein neuropathy from others immunoglobulin M-gammopathies, Haematologica, 2018, 103:e207-e210 http://dx.doi.org/10.3324/haematol.2017.177444

Yann Ferret et al., Multi-loci diagnosis of acute lymphoblastic leukaemia with high-throughput sequencing and bioinformatics analysis, British Journal of Haematology, 2016, 173, 413–420 http://dx.doi.org/10.1111/bjh.13981

Henrike J. Fischer et al., Modulation of CNS autoimmune responses by CD8+ T cells coincides with their oligoclonal expansion Journal of Neuroimmunology, 2015, S0165-5728(15)30065-5 http://dx.doi.org/10.1016/j.jneuroim.2015.10.020

Michaela Kotrova et al., The predictive strength of next-generation sequencing MRD detection for relapse compared with current methods in childhood ALL, Blood, 2015, 126:1045-1047 http://dx.doi.org/10.1182/blood-2015-07-655159

Ralf A. Linker et al., Thymocyte-derived BDNF influences T-cell maturation at the DN3/DN4 transition stage European Journal of Immunology, 2015, 45, 1326-1338 http://dx.doi.org/10.1002/eji.201444985

Mikaël Salson et al., High-throughput sequencing in acute lymphoblastic leukemia: Follow-up of minimal residual disease and emergence of new clones, Leukemia Research, 2017, 53, 1–7 http://dx.doi.org/10.1016/j.leukres.2016.11.009

Florian Scherer et al., Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA, Science Translational Medicine, 2016, 8, 364ra155 http://dx.doi.org/10.1126/scitranslmed.aai8545

Edit Porpaczy et al., Aggressive B-cell lymphomas in patients with myelofibrosis receiving JAK1/2 inhibitor therapy, Blood, 2018, https://dx.doi.org/10.1182/blood-2017-10-810739