|
Activity Number:
|
626
- Bayesian Methods in Genetics and Genomics
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Thursday, August 3, 2017 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Statistics in Genomics and Genetics
|
|
Abstract #324730
|
View Presentation
|
|
Title:
|
A Bayesian Multi-Dimensional Genotype Calling Algorithm for Multi-Allelic SNPs
|
|
Author(s):
|
Janice Brodsky* and Jeremy Gollub and Dorothy Oliver and Teresa Webster
|
|
Companies:
|
and Thermo Fisher Scientific and Thermo Fisher Scientific and Thermo Fisher Scientific
|
|
Keywords:
|
SNP ;
GWAS ;
multiallele ;
Bayesian
|
|
Abstract:
|
While the great majority of SNPs and indels in the human genome are biallelic, interest is growing in variants with multiple alternate alleles at one locus (multi-allelic SNP). In order to study and analyze the effect of multi-allelic SNPs on physical traits, they must be accurately and cleanly genotyped. We present a Bayesian genotype calling algorithm that was developed to genotype multiallelic markers in diploid genomes. It is intended to handle an arbitrary number of alleles, although there are practical limits in probe design. We present genotyping results on the Axiom® Genotyping Solution platform for several thousand SNPs with 2 or more alternate alleles, including quality-control checks and visualization software for multi-allelic SNPs.
|
Authors who are presenting talks have a * after their name.
