GRAMM: A new method for analysis of HLA in families

Zuriya Ansbacher-Feldman, Sapir Israeli, Martin Maiers, Loren Gragert, Dianne De Santis, Moshe Israeli, Yoram Louzoun

Research output: Contribution to journalArticlepeer-review


Recently, haplo-identical transplantation with multiple HLA mismatches has become a viable option for stem cell transplants. Haplotype sharing detection requires the imputation of donor and recipient. We show that even in high-resolution typing when all alleles are known, there is a 15% error rate in haplotype phasing, and even more in low-resolution typings. Similarly, in related donors, the parents' haplotypes should be imputed to determine what haplotype each child inherited. We propose graph-based family imputation (GRAMM) to phase alleles in family pedigree HLA typing data, and in mother-cord blood unit pairs. We show that GRAMM has practically no phasing errors when pedigree data are available. We apply GRAMM to simulations with different typing resolutions as well as paired cord-mother typings, and show very high phasing accuracy, and improved allele imputation accuracy. We use GRAMM to detect recombination events and show that the rate of falsely detected recombination events (false-positive rate) in simulations is very low. We then apply recombination detection to typed families to estimate the recombination rate in Israeli and Australian population datasets. The estimated recombination rate has an upper bound of 10%–20% per family (1%–4% per individual).

Original languageEnglish
Pages (from-to)477-488
Number of pages12
Issue number4
Early online date26 Apr 2023
StateE-pub ahead of print - 26 Apr 2023

Bibliographical note

Publisher Copyright:
© 2023 The Authors. HLA: Immune Response Genetics published by John Wiley & Sons Ltd.


  • HLA
  • HLA alleles imputation
  • haplotype phasing
  • pedigree analysis


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