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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 the VidjilNet consortium at Inria.

Vidjil is used in routine clinical practice in hospitals around the world, in particular for the diagnosis of patients suffering Acute Lymphoblastic Leukemia (ALL). Since 2015, around 50,000 routine samples were analyzed with Vidjil. As of 2024, Vidjil is used in 40+ studies on hemopathies (ALL, CLL, lymphomas, WM...) and immunology topics involving T-cell or B-cell repertoires. Vidjil was awarded an honourable mention at the French 2022 Open Science Awards for Open Source Research Software, in the Community category.

In addition to the core developers, we thank the many people who contribute to Vidjil across various aspects. Contributions span development, creation and maintenance of tests, documentation, as well as providing valuable usage reports, bug reports, and suggestions. See also codemeta.json.

Contact: Mathieu Giraud and Mikaël Salson

Vidjil core authors/developers⚓︎

  • Mathieu Giraud (CNRS), 2011-2024
  • Mikaël Salson (Univ. Lille), 2011-2024,
  • Marc Duez (Univ. Lille, CHU Lille, Inria), 2012-2016, 2019-2022
  • Tatiana Rocher (Univ. Lille), 2014-2017
  • Florian Thonier (CHU Necker, Inria), 2015-2024
  • Ryan Herbert (Inria), 2015-2020
  • Aurélien Béliard (CHU Lille), 2016-2017
  • Clément Chesnin (Inria), 2023-2024

Other contributors⚓︎

  • David Chatel, 2011-2012
  • Antonin Carette, 2014
  • Loïc Breton and Jordan Gilliot, 2014
  • François Dubiez, 2015-2016
  • Amina Boussalia and Fabien Fache, 2016
  • Eddy El Khatib and Nicolas Berveglieri, 2017
  • Téo Vasseur, 2017
  • Armand Bour, 2017
  • Joao Meidanis, 2018-2024
  • Cyprien Borée, 2018
  • Alexia Omietanski, 2018
  • Guilherme Giusti, 2020-2024
  • Axel Mercier, 2021
  • Agathe Bancquart, 2023

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

  • Yann Ferret (CHRU Lille), 2014-2015
  • Florian Thonier (Inserm, Paris Necker), 2015-2016

Acknowledgements⚓︎

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

  • Marine Armand
  • Jack Bartram
  • Aurélie Caillault
  • Frédéric Davi
  • Éric Delabesse
  • Yann Ferret
  • Alice Fievet
  • Martin Figeac
  • Nathalie Grardel
  • Michaela Kotrová
  • Anton W. Langerak
  • Yannick Le Bris
  • Anne Langlois de Septenville
  • Elizabeth Macintyre
  • David Margery
  • Cédric Pastoret
  • Claude Preudhomme
  • Shéhérazade Sebda

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

  • department of Hematology of CHRU Lille
  • Functional and Structural Genomic Platform (U. Lille 2, IFR-114, IRCL)
  • Institut Necker Enfants Malades, Paris
  • EuroClonality-NGS working group

Funding⚓︎

The development of Vidjil is funded by:

  • Région Nord-Pas-de-Calais/Hauts-de-France, 2012-2017
  • Université Lille 1, 2014-2017
  • SIRIC ONCOLille (Grant INCa-DGOS-Inserm 6041), 2014-2017
  • Inria Lille, 2015-2018
  • InCA, 2016-2019
  • VidjilNet consortium at Inria, 2018-2024

References⚓︎

If you use vidjil-algo, please cite [Giraud, Salson 2014]. If you use the web platform, please cite [Duez 2016]. Reference for protocols are [Villarese 2022] (marker identification in ALL) and [Septenville 2022] (assessment of mutational status in CLL).

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

Patrick Villarese et al., One-Step Next-Generation Sequencing of Immunoglobulin and T-Cell Receptor Gene Recombinations for MRD Marker Identification in Acute Lymphoblastic Leukemia, Immunogenetics, Methods in Molecular Biology 2453, 2022, pp. 43-59, http://dx.doi.org/10.1007/978-1-0716-2115-8_3

Anne Langlois de Septenville et al., Immunoglobulin Gene Mutational Status Assessment by Next Generation Sequencing in Chronic Lymphocytic Leukemia, Immunogenetics, Methods in Molecular Biology 2453, 2022, pp. 153-167, http://dx.doi.org/10.1007/978-1-0716-2115-8_10

Some publications using Vidjil⚓︎

  1. Chrystelle Abdo et al., Caution encouraged in next-generation sequencing immunogenetic analyses in acute lymphoblastic leukemia, Blood, 2020, 136(9):1105–1107, https://doi.org/10.1182/blood.2020005613
  2. 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
  3. Kristian Assing et al., A Novel CDC42 Variant with Impaired Thymopoiesis, IL-7R Signaling, PAK1 Binding, and TCR Repertoire Diversity Journal of Clinical Immunology, 2023, https://doi.org/10.1007/s10875-023-01561-0
  4. Jack Bartram et al., High throughput sequencing in acute lymphoblastic leukemia reveals clonal architecture of central nervous system and bone marrow compartments, Haematologica, 2018, https://dx.doi.org/10.3324%2Fhaematol.2017.174987
  5. Sébastien Bender et al., Immunoglobulin variable domain high-throughput sequencing reveals specific novel mutational patterns in POEMS syndrome, Blood, 2020, https://doi.org/10.1182/blood.2019004197
  6. Marie-Laure Boulland et al., Reliable IGHV status assessment by next generation sequencing in routine practice for chronic lymphocytic leukemia, Leukemia & Lymphoma, 2021, https://doi.org/10.1080/10428194.2021.1933476
  7. Estelle Bourbon et al., Next-CLL: A New Next-Generation Sequencing–Based Method for Assessment of IGHV Gene Mutational Status in Chronic Lymphoid Leukemia, The Journal of Molecular Diagnostics, 2023, https://doi.org/10.1016/j.jmoldx.2023.01.009
  8. Monika Brüggemann et al., on behalf of the EuroClonality-NGS working group, Standardized next-generation sequencing of immunoglobulin and T-cell receptor gene recombinations for MRD marker identification in acute lymphoblastic leukaemia; a EuroClonality-NGS validation study, Leukemia, 2019, 33, 2241–2253, https://doi.org/10.1038/s41375-019-0496-7
  9. Roberta Cavagna et al., Capture-based Next-Generation Sequencing Improves the Identification of Immunoglobulin/T-Cell Receptor Clonal Markers and Gene Mutations in Adult Acute Lymphoblastic Leukemia Patients Lacking Molecular Probes, Cancers, 2020, 12(6), 1505, https://doi.org/10.3390/cancers12061505
  10. Rodolfo P. Correia et al., High‐throughput sequencing of immunoglobulin heavy chain for minimal residual disease detection in B‐lymphoblastic leukemia, Int. Journal of Laboratory Hematology, 2021, https://doi.org/10.1111/ijlh.13453
  11. Frédéric Davi et al., on behalf of ERIC, the European Research Initiative on CLL, and the EuroClonality-NGS Working Group, Immunoglobulin gene analysis in chronic lymphocytic leukemia in the era of next generation sequencing, Leukemia, 2020, https://doi.org/10.1038/s41375-020-0923-9
  12. Rachel Dobson et al., Widespread in situ follicular neoplasia in patients who subsequently developed follicular lymphoma, The Journal of Pathology, 2021, https://doi.org/10.1002/path.5861
  13. 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, https://hal.archives-ouvertes.fr/hal-01279160
  14. 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
  15. Navarro Nilo Giusti et al., Test trial of spike-in immunoglobulin heavy-chain (IGH) controls for next generation sequencing quantification of minimal residual disease in acute lymphoblastic leukaemia, British Journal of Haematology, 2020, 189: e150-e154, https://doi.org/10.1111/bjh.16571
  16. Heraud et al., Monoclonal B-cell lymphocytosis with a non-CLL immunophenotype–Review of 34 cases Annales de Biologie Clinique, 2023, https://www.jle.com./fr/revues/abc/e-docs/monoclonal_b_cell_lymphocytosis_with_a_non_cll_immunophenotype_review_of_34_cases_330642/article.phtml?tab=texte
  17. -Jung Huang et al., Evaluation of next-generation sequencing for measurable residual disease monitoring in three major fusion transcript subtypes of B-precursor acute lymphoblastic leukaemia, Pathology, 2024, https://doi.org/10.1016/j.pathol.2024.02.008
  18. Izotova et al., Long-term lymphoid progenitors independently sustain naïve T and NK cell production in humans, Nature Communications, 2021, https://doi.org/10.1038/s41467-021-21834-9
  19. Vincent Javaugue et al., RNA-based immunoglobulin repertoire sequencing is a new tool for the management of monoclonal gammopathy of renal (kidney) significance Kidney International, 2022 https://www.sciencedirect.com/science/article/abs/pii/S0085253821010334
  20. Irene Jo et al., Considerations for monitoring minimal residual disease using immunoglobulin clonality in patients with precursor B-cell lymphoblastic leukemia, Clinica Chimica Acta, 2019, https://doi.org/10.1016/j.cca.2018.10.037
  21. Takashi Kanamori et al., Genomic analysis of multiple myeloma using targeted capture sequencing in the Japanese cohort, British Journal of Haematology, 2020, https://doi.org/10.1111/bjh.16720
  22. Kim et al., Adult T-cell acute lymphoblastic leukemias with IL7R pathway mutations are slow-responders who do not benefit from allogeneic stem-cell transplantation, Leukemia, 2020, 34, 1730-1740, https://dx.doi.org/10.1038/s41375-019-0685-4
  23. Kimura et al., Identification of Clonal Immunoglobulin λ Light-Chain Gene Rearrangements in AL Amyloidosis Using Next-Generation Sequencing, Experimental Hematology, 2021, 101:34-41.e4 https://doi.org/10.1016/j.exphem.2021.08.001
  24. 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
  25. Kotrova et al., Next‐generation amplicon TRB locus sequencing can overcome limitations of flow‐cytometric Vβ expression analysis and confirms clonality in all T‐cell ,prolymphocytic leukemia cases, Cytometry Part A, 93(11):1118-1124, 2018, http://dx.doi.org/10.1002/cyto.a.23604
  26. Anton W. Langerak, High-Throughput Immunogenetics for Clinical and Research Applications in Immunohematology: Potential and Challenges, Journal of Immunology, 2017, 198(10):3765-3774, https://dx.doi.org/10.4049/jimmunol.1602050
  27. Le Bris et al., Single Capture High Throughput Sequencing Assay for Combined V(D)J Clonality Analysis and Oncogene Mutations in the Diagnosis of T and B Lymphoid Malignancies, ASH 2021, Blood, 138(S1):2404, https://doi.org/10.1182/blood-2021-151083
  28. Zhenhua Li et al., Identifying IGH disease clones for MRD monitoring in childhood B-cell acute lymphoblastic leukemia using RNA-Seq, Leukemia, 2020, 34:2418-2429, http://dx.doi.org/10.1038/s41375-020-0774-4
  29. 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
  30. Liang Oon et al., T-Cell Lymphoma Clonality by Copy Number Variation Analysis of T-Cell Receptor Genes, Cancers, 2021, 13(2), 340, https://dx.doi.org/10.3390/cancers13020340
  31. Materna et al., The immunopathological landscape of human pre-TCRα deficiency: From rare to common variants, Science, 2024, https://doi.org/10.1126/science.adh4059
  32. Alejandro Medina et al., Comparison of next-generation sequencing (NGS) and next-generation flow (NGF) for minimal residual disease (MRD) assessment in multiple myeloma, Blood Cancer Journal, 10, 108, 2020, https://doi.org/10.1038/s41408-020-00377-0
  33. Nishijima et al., Capture Sequencing Is a Useful Method for Comprehensive Clonality Analysis Based on Ig/TCR Gene Rearrangements in Acute Lymphoblastic Leukemia, ASH 2018, Blood, 132(S1):1543, https://doi.org/10.1182/blood-2018-99-115624
  34. Piedrafita et al., Spectrum of Kidney Disorders Associated with T-Cell Immunoclones, Journal of Clinical Medicine, 2022, 11(3), 604, https://doi.org/10.3390/jcm11030604
  35. 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
  36. Pastoret et al., Molecular mechanisms underlying transformation of large granular lymphocytic leukemia to high-grade T-cell lymphoma, Leukemia, 2023, https://www.nature.com/articles/s41375-023-01922-z
  37. Olivier Pellé et al., Combined germline and somatic human FADD mutations cause autoimmune lymphoproliferative syndrome, Journal of Allergy and Clinical Immunology, 2024, https://doi.org/10.1016/j.jaci.2023.09.028
  38. Maria Rodrigo Riestra et al., Human Autosomal Recessive DNA Polymerase Delta 3 Deficiency Presenting as Omenn Syndrome, Journal of Clinical Immunology, 2024, https://doi.org/10.1007/s10875-023-01627-z
  39. 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
  40. Masashi Sanada et al., Targeted-Capture Sequencing Is a Useful Method for MRD Markers Screening in KMT2A (MLL) Rearranged Leukemia, ASH 2019, Blood, 134(S1):2759, https://doi.org/10.1182/blood-2019-125421
  41. 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
  42. V. Seitz et al., Evidence for a role of RUNX1 as recombinase cofactor for TCRβ rearrangements and pathological deletions in ETV6-RUNX1 ALL Scientific Reports, 2020, 10:10024, https://doi.org/10.1038/s41598-020-65744-0
  43. Udo zur Stadt et al., Characterization of novel, recurrent genomic rearrangements as sensitive MRD targets in childhood B-cell precursor ALL, Blood Cancer Journal, 2019, https://doi.org/10.1038/s41408-019-0257-x
  44. Lucia Stranavova et al., Heterologous Cytomegalovirus and Allo-Reactivity by Shared T Cell Receptor Repertoire in Kidney Transplantation, Frontiers in Immunology, 2019, https://doi.org/10.3389/fimmu.2019.02549
  45. Manuela Tosi et al., MRD-Based Therapeutic Decisions in Genetically Defined Subsets of Adolescents and Young Adult Philadelphia-Negative ALL Cancers 2021, 13(9), 2108, https://doi.org/10.3390/cancers13092108
  46. Amelie Trinquand et al., Toward Pediatric T Lymphoblastic Lymphoma Stratification Based on Minimal Disseminated Disease and NOTCH1/FBXW7 Status, HemaSphere, 2021, https://doi.org/10.1097/hs9.0000000000000641
  47. Patrik Villarèse et al., One step next generation sequencing of immunoglobulin and T-cell receptor gene recombinations for MRD marker identification in acute lymphoblastic leukemia, ed. Anton W. Langerak, Methods in Molecular Biology, 2022, https://link.springer.com/protocol/10.1007/978-1-0716-2115-8_3
  48. Christine Wennerås et al., Infection with Neoehrlichia mikurensis promotes the development of malignant B-cell lymphomas , British Journal of Haematology, 2023, https://doi.org/10.1111/bjh.18652
  49. Gary Wright et al., Clinical benefit of a high‐throughput sequencing approach for minimal residual disease in acute lymphoblastic leukemia, Pediatric Blood & Cancer, 2019, https://doi.org/10.1002/pbc.27787
  50. Wen‐Qing Yao et al., Angioimmunoblastic T‐cell lymphoma contains multiple clonal T‐cell populations derived from a common TET2 mutant progenitor cell, The Journal of Pathology, 2019, https://doi.org/10.1002/path.5376
  51. Yasuda et al., Clinical utility of target capture‐based panel sequencing in hematological malignancies: A multicenter feasibility study, Cancer Science, 2020, 111(9):3367-3378, https://dx.doi.org/10.1111/cas.14552