VDJML: A file format with tools for capturing the results of inferring immune receptor rearrangements

BMC Bioinformatics

Volumn 17, Issue , 2016, Pages

  Toby, Inimary T ^a   Levin, Mikhail K ^b   Salinas, Edward A ^c   Christley, Scott ^a   Bhattacharya, Sanchita ^d   Breden, Felix ^e   Buntzman, Adam ^f   Corrie, Brian ^g   Fonner, John ^h   Gupta, Namita T ⁱ   Hershberg, Uri ^j   Marthandan, Nishanth ^e   Rosenfeld, Aaron ^k   Rounds, William ^l   Rubelt, Florian ^m   Scarborough, Walter ^h   Scott, Jamie K ^e   Uduman, Mohamed ⁿ   Vander Heiden, Jason A ⁱ   Scheuermann, Richard H ^o,p,q   Monson, Nancy ^l   Kleinstein, Steven H ^i,n   Cowell, Lindsay G ^a   more..

^a UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

^b Bank of America Corp   (United States)

^c BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e SIMON FRASER UNIVERSITY   (Canada)

^f UNIVERSITY OF ARIZONA COLLEGE OF MEDICINE   (United States)

^g UNIVERSITY OF AUCKLAND   (New Zealand)

^h Texas Advanced Computing Center   (United States)

ⁱ YALE UNIVERSITY   (United States)

^j DREXEL UNIVERSITY COLLEGE OF MEDICINE   (United States)

^k DREXEL UNIVERSITY   (United States)

^l UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

^m STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

ⁿ YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^o J CRAIG VENTER INSTITUTE   (United States)

^p UNIVERSITY OF CALIFORNIA   (United States)

^q LA JOLLA INSTITUTE FOR ALLERGY AND IMMUNOLOGY   (United States)

more..

Author keywords

Antigen receptor repertoire; C++; Data sharing; Data standards; Immune repertoire; Python; Repertoire profiling; XML

Indexed keywords

ANTIGENS; CESIUM; CLINICAL RESEARCH; COMPUTER SOFTWARE; GENES; LYMPHOCYTES; XML;

ANTIGEN RECEPTORS; DATA SHARING; DATA STANDARDS; IMMUNE REPERTOIRE; PYTHON; REPERTOIRE PROFILING;

C++ (PROGRAMMING LANGUAGE);

IMMUNOGLOBULIN RECEPTOR;

GENETICS; GENOMICS; HUMAN; INFORMATION DISSEMINATION; PROCEDURES; SOFTWARE; VDJ RECOMBINATION;

GENOMICS; HUMANS; INFORMATION DISSEMINATION; RECEPTORS, IMMUNOLOGIC; SOFTWARE; V(D)J RECOMBINATION;

EID: 84990817455     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-1214-3     Document Type: Article

References (41)

1. Tonegawa S. Somatic generation of antibody diversity. Nature. 1983;302(5909):575-81.
2. Schatz DG, Oettinger MA, Schlissel MS. V(D)J recombination: molecular biology and regulation. Annu Rev Immunol. 1992;10:359-83.
3. Reynaud CA, et al. Formation of the chicken B-cell repertoire: ontogenesis, regulation of Ig gene rearrangement, and diversification by gene conversion. Adv Immunol. 1994;57:353-78.
4. Berek C, Milstein C. The dynamic nature of the antibody repertoire. Immunol Rev. 1988;105:5-26.
5. Lythe G, et al. How many TCR clonotypes does a body maintain? J Theor Biol. 2016;389:214-24.
6. Warren RL, et al. Exhaustive T-cell repertoire sequencing of human peripheral blood samples reveals signatures of antigen selection and a directly measured repertoire size of at least 1 million clonotypes. Genome Res. 2011;21(5):790-7.
7. Hou XL, et al. Current status and recent advances of next generation sequencing techniques in immunological repertoire. Genes Immun. 2016;17(3):153-64.
8. Georgiou G, et al. The promise and challenge of high-throughput sequencing of the antibody repertoire. Nat Biotechnol. 2014;32(2):158-68.
9. Kirsch I, Vignali M, Robins H. T-cell receptor profiling in cancer. Mol Oncol. 2015;9(10):2063-70.
10. Calis JJ, Rosenberg BR. Characterizing immune repertoires by high throughput sequencing: strategies and applications. Trends Immunol. 2014;35(12):581-90.
11. Yaari G, Kleinstein SH. Practical guidelines for B-cell receptor repertoire sequencing analysis. Genome Med. 2015;7:121.
12. Ye J, et al. IgBLAST: an immunoglobulin variable domain sequence analysis tool. Nucleic Acids Res. 2013;41(Web Server issue):W34-40.
13. Alamyar E, et al. IMGT((R)) tools for the nucleotide analysis of immunoglobulin (IG) and T cell receptor (TR) V-(D)-J repertoires, polymorphisms, and IG mutations: IMGT/V-QUEST and IMGT/HighV-QUEST for NGS. Methods Mol Biol. 2012;882:569-604.
14. Volpe JM, Cowell LG, Kepler TB. SoDA: implementation of a 3D alignment algorithm for inference of antigen receptor recombinations. Bioinformatics. 2006;22(4):438-44.
15. Munshaw S, Kepler TB. SoDA2: a Hidden Markov Model approach for identification of immunoglobulin rearrangements. Bioinformatics. 2010;26(7):867-72.
16. Gaeta BA, et al. iHMMune-align: hidden Markov model-based alignment and identification of germline genes in rearranged immunoglobulin gene sequences. Bioinformatics. 2007;23(13):1580-7.
17. Wang X, et al. Ab-origin: an enhanced tool to identify the sourcing gene segments in germline for rearranged antibodies. BMC Bioinformatics. 2008;9 Suppl 12:S20.
18. Ohm-Laursen L, et al. No evidence for the use of DIR, D-D fusions, chromosome 15 open reading frames or VH replacement in the peripheral repertoire was found on application of an improved algorithm, JointML, to 6329 human immunoglobulin H rearrangements. Immunology. 2006;119(2):265-77.
19. Souto-Carneiro MM, et al. Characterization of the human Ig heavy chain antigen binding complementarity determining region 3 using a newly developed software algorithm, JOINSOLVER. J Immunol. 2004;172(11):6790-802.
20. Zhao S, Lu J. A germline knowledge based computational approach for determining antibody complementarity determining regions. Mol Immunol. 2010;47(4):694-700.
21. Chen Z, et al. Clustering-based identification of clonally-related immunoglobulin gene sequence sets. Immunome Res. 2010;6 Suppl 1:S4.
22. Barak M, et al. IgTree: creating Immunoglobulin variable region gene lineage trees. J Immunol Methods. 2008;338(1-2):67-74.
23. Gupta NT, et al. Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. Bioinformatics. 2015;31(20):3356-8.
24. Vander Heiden JA, et al. pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires. Bioinformatics. 2014;30(13):1930-2.
25. Bolotin DA, et al. MiTCR: software for T-cell receptor sequencing data analysis. Nat Methods. 2013;10(9):813-4.
26. Cortina-Ceballos B, et al. Reconstructing and mining the B cell repertoire with ImmunediveRsity. MAbs. 2015;7(3):516-24.
27. D'Angelo S, et al. The antibody mining toolbox: an open source tool for the rapid analysis of antibody repertoires. MAbs. 2014;6(1):160-72.
28. Imkeller K, et al. sciReptor: analysis of single-cell level immunoglobulin repertoires. BMC Bioinformatics. 2016;17:67.
29. Kuchenbecker L, et al. IMSEQ--a fast and error aware approach to immunogenetic sequence analysis. Bioinformatics. 2015;31(18):2963-71.
30. Nazarov VI, et al. tcR: an R package for T cell receptor repertoire advanced data analysis. BMC Bioinformatics. 2015;16:175.
31. Ralph DK, Matsen FAt. Consistency of VDJ rearrangement and substitution parameters enables accurate B cell receptor sequence annotation. PLoS Comput Biol. 2016;12(1):e1004409.
32. Safonova Y, et al. IgRepertoireConstructor: a novel algorithm for antibody repertoire construction and immunoproteogenomics analysis. Bioinformatics. 2015;31(12):i53-61.
33. Schaller S, et al. ImmunExplorer (IMEX): a software framework for diversity and clonality analyses of immunoglobulins and T cell receptors on the basis of IMGT/HighV-QUEST preprocessed NGS data. BMC Bioinformatics. 2015;16:252.
34. Thomas N, et al. Decombinator: a tool for fast, efficient gene assignment in T-cell receptor sequences using a finite state machine. Bioinformatics. 2013;29(5):542-50.
35. Zhang W, et al. IMonitor: a robust pipeline for TCR and BCR repertoire analysis. Genetics. 2015;201(2):459-72.
36. Brusic V, et al. Computational resources for high-dimensional immune analysis from the Human Immunology Project Consortium. Nat Biotechnol. 2014;32(2):146-8.
37. Bray T. Extensible Markup Language (XML) 1.0; W3C Recommendation 10-February-1998. W3C 1998 4/27/2016]; Available from: https://www.w3.org/TR/1998/REC-xml-19980210.
38. Achard F, Vaysseix G, Barillot E. XML, bioinformatics and data integration. Bioinformatics. 2001;17(2):115-25.
39. Bhattacharya S, et al. ImmPort: disseminating data to the public for the future of immunology. Immunol Res. 2014;58(2-3):234-9.
40. Rubelt F, et al. Individual heritable differences result in unique cell lymphocyte receptor repertoires of naive and antigen-experienced cells. Nat Commun. 2016;7:11112.
41. Gadala-Maria D, et al. Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles. Proc Natl Acad Sci U S A. 2015;112(8):E862-70.