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RDI specifications


Unique identifier OMICS_20884
Name RDI
Alternative name Repertoire Dissimilarity Index
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 0.9.0
Stability Stable
Maintained Yes




No version available


  • person_outline Mark Davis

Publication for Repertoire Dissimilarity Index

RDI citations


Analyzing Immunoglobulin Repertoires

Front Immunol
PMCID: 5861150
PMID: 29593723
DOI: 10.3389/fimmu.2018.00462

[…] Repertoire dissimilarity index compares Ig repertoire based on usage of V, D, or J (, ). It is a non-parametric method, which tries to circumvent the problem of varying number of sequences in differen […]


Computational Strategies for Dissecting the High Dimensional Complexity of Adaptive Immune Repertoires

Front Immunol
PMCID: 5826328
PMID: 29515569
DOI: 10.3389/fimmu.2018.00224

[…] incorporating both binned sequence features (e.g., clone sequences, germline genes) and their frequency for measuring the impact of heritable factors on VDJ recombination and thymic selection. Their Repertoire Dissimilarity Index consists of a non-parametric Euclidian-distance-based bootstrapped subsampling approach, which enables the quantification of the average variation between repertoires (, […]


Individual heritable differences result in unique cell lymphocyte receptor repertoires of naïve and antigen experienced cells

Nat Commun
PMCID: 5191574
PMID: 27005435
DOI: 10.1038/ncomms11112

[…] for representative examples and ), and 0.75–0.90 in naïve CD4+ T cells and CD8+ T cells. However, we found that this correlation was always highest among MZ twins. To quantify this, we developed the Repertoire Dissimilarity Index (RDI) as a measure of distance between repertoires. This metric uses random subsampling to control for heterogeneity in repertoire sizes between individuals, allowing di […]

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RDI institution(s)
Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA; Genentech, Inc., South San Francisco, CA, USA; Interdepartmental Program in Computational Biology and Bioinformatics, Department of Computational Biology & Bioinformatics, Yale University, New Haven, CT, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA; Institute of Immunity, Department of Microbiology and Immunology, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA
RDI funding source(s)
Supported by the National Institutes of Health, specifically the National Institute of Allergy and Infectious Diseases grants U19AI057229, U19AI090019 and the Howard Hughes Medical Institute; 1UL1 RR025744 for the Stanford Center for Clinical and Translational Education and Research (Spectrum) from the National Center for Research Resources; the Bioinformatics Support Contract (BISC)HHSN272201200028C; the “Molecular and Cellular Immunobiology” training grant (5 T32 AI07290); the National Library of Medicine grant T15LM07056.

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