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Related Experiment Video

Updated: Apr 12, 2026

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
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HTJoinSolver: Human immunoglobulin VDJ partitioning using approximate dynamic programming constrained by conserved

Daniel E Russ1, Kwan-Yuet Ho2, Nancy S Longo3

  • 1Division of Computational Bioscience, Center for Information Technology, NIH, 12 South Drive, Bethesda, MD, 20892, USA. druss@mail.nih.gov.

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|May 24, 2015
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Summary

We developed a new approximate dynamic programming method to accurately align immunoglobulin (Ig) gene segments, improving V-segment matching from 61% to over 99% even with insertions and deletions.

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Area of Science:

  • Immunology
  • Bioinformatics
  • Genomics

Background:

  • Partitioning human immunoglobulin variable regions into V, D, and J segments is crucial for sequence analysis.
  • Existing algorithms face challenges with insertions and deletions (indels) in rearranged immunoglobulin (Ig) genes.
  • High-throughput sequencing generates large datasets requiring efficient analysis tools.

Purpose of the Study:

  • To introduce a novel approximate dynamic programming method for improved alignment of V-segments in rearranged Ig genes.
  • To enhance the JOINSOLVER algorithm for processing sequences with indels.
  • To improve the efficiency of Ig gene segment analysis for large datasets.

Main Methods:

  • Developed a novel approximate dynamic programming algorithm using conserved immunoglobulin gene motifs.
  • Enhanced the JOINSOLVER algorithm to process sequences containing insertions and/or deletions (indels).
  • Evaluated performance using simulations with rearrangements and indels, and compared against the Stanford.S22 human Ig dataset.

Main Results:

  • Achieved over 99% V-matching success rate for sequences with indels, a significant improvement from 61% in the original algorithm.
  • Demonstrated improved alignment of human VDJ rearrangements compared to the initial JOINSOLVER algorithm.
  • The new algorithm, HTJoinSolver, accurately identifies V- and J-segments with indels in mutated sequences.

Conclusions:

  • HTJoinSolver accurately and rapidly identifies V- and J-segments with indels in mutated sequences (up to 30% mutation probability).
  • D-segment identification remains challenging, even at 20% mutation probability.
  • Alignment score positively correlates with the probability of correctly matching V, D, and J segments.