VDJdb

VDJdb provides a curated database of T-cell receptor (TCR) sequences linked to cognate antigens to support analysis of TCR specificity and immune recognition.


Key Features:

  • Curated TCR–Antigen Reference Dataset: Contains experimentally validated T-cell receptor sequences associated with their cognate antigens.
  • Expanded TCR Sequence Collection: Incorporates a substantially increased set of TCR sequences and antigen associations derived from published studies.
  • Batch Annotation of TCR Repertoire Data: Supports annotation of TCR repertoire sequencing datasets by matching sequences against database entries.
  • TCR Motif Compendium: Provides a curated set of high-confidence TCR sequence motifs derived from bioinformatic motif mining.
  • Motif-Based Specificity Analysis: Enables matching of TCR sequences against known motifs to explore potential antigen specificity.

Scientific Applications:

  • TCR Specificity Analysis: Identifies antigen specificities associated with T-cell receptor sequences.
  • Adaptive Immune Repertoire Research: Analyzes TCR repertoire sequencing datasets to study antigen recognition patterns.
  • Machine Learning Model Development: Uses curated TCR motifs and sequence–antigen associations to train TCR specificity prediction models.

Methodology:

VDJdb curates experimentally validated TCR–antigen associations, mines high-confidence TCR sequence motifs using bioinformatic methods, and enables annotation of TCR repertoire sequencing datasets by matching sequences and motifs against the database.

Topics

Details

Added:
1/9/2020
Last Updated:
1/16/2021

Operations

Publications

Bagaev DV, Vroomans RMA, Samir J, Stervbo U, Rius C, Dolton G, Greenshields-Watson A, Attaf M, Egorov ES, Zvyagin IV, Babel N, Cole DK, Godkin AJ, Sewell AK, Kesmir C, Chudakov DM, Luciani F, Shugay M. VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium. Nucleic Acids Research. 2019;48(D1):D1057-D1062. doi:10.1093/nar/gkz874. PMID:31588507. PMCID:PMC6943061.

PMID: 31588507
Funding: - Russian Science Foundation: 17-15-01495