A V-(D)-J partitioning GUI application powered by novel approximate dynamic programming method that uses conserved immunoglobulin gene motifs to improve performance of aligning V-segments of rearranged immunoglobulin (Ig) genes. The new algorithm enhances the former JOINSOLVER algorithm by processing sequences with insertions and/or deletions (indels) and improves the efficiency for large datasets provided by high throughput sequencing. According to simulations, which include rearrangements with indels, the V-matching success rate improved from 61% for partial alignments of sequences with indels in the original algorithm to over 99% in the approximate algorithm. An improvement in the alignment of human VDJ rearrangements over the initial JOINSOLVER algorithm was also seen when compared to the Stanford.S22 human Ig dataset with an online VDJ partitioning software evaluation tool. HTJoinSolver can rapidly identify V- and J-segments with indels to high accuracy for mutated sequences when the mutation probability is around 30% and 20% respectively. The D-segment is much harder to fit even at 20% mutation probability. For all segments, the probability of correctly matching V, D, and J increases with our alignment score.

User report

0 user reviews

0 user reviews

No review has been posted.

HTJoinSolver forum

No open topic.

HTJoinSolver versioning

No versioning.

HTJoinSolver classification

  • Animals
  • Fungi
  • Plants
  • Protists

HTJoinSolver specifications

Software type:
Restrictions to use:
Output data:
V-D-J segment partitioning
Operating system:
Unix/Linux, Mac OS, Windows
Apache License version 2.0
HTJoinSolver version 1.0
Graphical user interface
Input format:
Biological technology:
Illumina, Roche
Programming languages:
Computer skills:

HTJoinSolver support



  • Daniel E. Russ <>




Division of Computational Bioscience, Center for Information Technology, NIH, Bethesda, MD, USA; Vaccine Research Center, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, USA

Funding source(s)

This work was supported by the Intramural Research Programs of the Center for Information Technology, National Institutes of Health and the Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health.

Link to literature

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.