Related Experiment Video
Updated: Jun 2, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
Fast, exact linkage analysis for categorical traits on arbitrary pedigree designs
Abra Brisbin1, Jenifer Cruickshank, N Sydney Moïse
1Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA. abrisbin@gmail.com
Abstract:
Multi-symptom diseases without a consistent continuous measurement of severity may be best understood with a categorical interpretation. In this paper, we present LOCate v.2, a fast, exact algorithm for linkage analysis of all types of categorical traits, both ordinal and nominal. Our method is able to incorporate missing data and analyze complex genealogical structure, including inbreeding loops. LOCate v.2 computes exact likelihoods efficiently through an elimination algorithm, similar to that used by Superlink for binary traits. We compare LOCate v.2 to LOT and QTLlink, two existing methods of linkage analysis for ordinal traits. We find that LOCate v.2 outperforms both methods when used to analyze simulated nominal traits. In addition, LOCate v.2 performs as well as QTLlink on simulated ordinal traits, and better than LOT due to the necessity of cutting large pedigrees for analysis in LOT. To demonstrate the versatility of LOCate v.2, we conduct an ordinal and nominal linkage analysis of ventricular arrhythmias in a large, inbred pedigree of German Shepherd dogs. We find that a trichotomous ordinal or nominal interpretation strengthens the evidence in favor of linkage to a region on chromosome 6, and provides new evidence of linkage to a region on chromosome 11. LOCate v.2 is a unified, fast, and robust method for linkage analysis of ordinal and nominal traits which will be valuable to researchers interested in investigating any type of categorical trait.
More Related Videos
Related Concept Videos
Pedigree Analysis
Pedigree Analysis
Dihybrid Crosses
Multiple Allele Traits
Multiple Allele Traits
Evolutionary Relationships through Genome Comparisons

