Ab-origin: An enhanced tool to identify the sourcing gene segments in germline for rearranged antibodies

Xiaojing Wang, Di Wu, Siyuan Zheng, Jing Sun, Lin Tao, Yixue Li, Zhiwei Cao

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


Background: In the adaptive immune system, variable regions of immunoglobulin (IG) are encoded by random recombination of variable (V), diversity (D), and joining (J) gene segments in the germline. Partitioning the functional antibody sequences to their sourcing germline gene segments is vital not only for understanding antibody maturation but also for promoting the potential engineering of the therapeutic antibodies. To date, several tools have been developed to perform such "trace-back" calculations. Yet, the predicting ability and processing volume of those tools vary significantly for different sets of data. Moreover, none of them give a confidence for immunoglobulin heavy diversity (IGHD) identification. Developing fast, efficient and enhanced tools is always needed with the booming of immunological data. Results: Here, a program named Ab-origin is presented. It is designed by batch query against germline databases based on empirical knowledge, optimized scoring scheme and appropriate parameters. Special efforts have been paid to improve the identification accuracy of the short and volatile region, IGHD. In particular, a threshold score for certain sensitivity and specificity is provided to give the confidence level of the IGHD identification. Conclusion: When evaluated using different sets of both simulated data and experimental data, Ab-origin outperformed all the other five popular tools in terms of prediction accuracy. The features of batch query and confidence indication of IGHD identification would provide extra help to users. The program is freely available at http://mpsq.biosino.org/ ab-origin/supplementary.html.

Original languageEnglish (US)
Article numberS20
JournalBMC bioinformatics
Issue numberSUPPL. 12
StatePublished - Dec 12 2008
Externally publishedYes

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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