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PreprintCC BYbioRxiv

Bundling Alleles Within Haplotype Blocks Improves QTL Detection Under Allelic Heterogeneity

  1. 1HZPC Research B.V.

Abstract

Allelic heterogeneity is a term from genetics which means that alleles that differ in primary sequence can have a similar phenotypic outcome. In other words, they are functional equivalents, and they naturally appear through convergent evolution under selection. Current GWAS has trouble detecting these instances, as allelic heterogeneity leads to signal dilution in these analyses, often leading to a LOD score that stays below detection thresholds. In this paper, we show a method that can overcome this problem by bundling haplotypes into Artificial Combined Markers. The created marker matrix can then easily be used in existing GWAS software.

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BibTeX
@misc{oome2026bundling,
  title = {{Bundling Alleles Within Haplotype Blocks Improves QTL Detection Under Allelic Heterogeneity}},
  author = {S. Oome and M. Ghanbari},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.04.749340},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.04.749340v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Bundling Alleles Within Haplotype Blocks Improves QTL Detection Under Allelic Heterogeneity
AU  - S. Oome
AU  - M. Ghanbari
PY  - 2026
DA  - 2026/09/04
PB  - bioRxiv
DO  - 10.64898/2026.09.04.749340
UR  - https://www.biorxiv.org/content/10.64898/2026.09.04.749340v1
AB  - Allelic heterogeneity is a term from genetics which means that alleles that differ in primary sequence can have a similar phenotypic outcome. In other words, they are functional equivalents, and they naturally appear through convergent evolution under selection. Current GWAS has trouble detecting these instances, as allelic heterogeneity leads to signal dilution in these analyses, often leading to a LOD score that stays below detection thresholds. In this paper, we show a method that can overcome this problem by bundling haplotypes into Artificial Combined Markers. The created marker matrix can then easily be used in existing GWAS software.
ER  -