Bioinformatics Seminars

Bioinformatics Seminar

Time: 11:00am Tuesdays.
Venue:
Zoom Webinar

8 June 2021

A hidden Markov model to identify inherited disease-causing mutations using shared genetic markers

Erandee Robertson
WEHI Population Health & Immunity

Individuals who inherit the same genetic mutation from a common ancestor also share genomic regions either side of the shared disease-causing variant. This suggests that the presence of a disease-causing genetic variant can be inferred by assessing identity by descent sharing of the variant-associated haplotype between an individual known to have the disease-causing mutation and a patient with unknown aetiology.

We developed a statistical algorithm called FoundHaplo, which is a hidden Markov model designed to identify individuals with inherited disease-causing genetic variants using SNP data.

Repeat expansions cause multiple diseases and are often inherited due to strong founder effects. We performed a comprehensive simulation study to evaluate the performance for 28 known repeat expansion diseases. FoundHaplo correctly predicted 94% of simulated samples sharing a region of at least 1 cM surrounding the disease-causing variant and 100% of simulated samples sharing 2 cM or more.

Using FoundHaplo, we searched for putative variant-associated haplotypes in SNP data from 1,573 individuals with epilepsy and identified two individuals already known to carry a mutation in SCN1B gene from prior genetic analyses.


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