Integration of SNP genotyping confidence scores in IBD inference
Author(s) -
Barak Markus,
Ohad S. Birk,
Dan Geiger
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr486
Subject(s) - inference , computer science , genotyping , snp , confidence interval , artificial intelligence , machine learning , computational biology , single nucleotide polymorphism , data mining , statistics , biology , genetics , mathematics , genotype , gene
High-throughput single nucleotide polymorphism (SNP) arrays have become the standard platform for linkage and association analyses. The high SNP density of these platforms allows high-resolution identification of ancestral recombination events even for distant relatives many generations apart. However, such inference is sensitive to marker mistyping and current error detection methods rely on the genotyping of additional close relatives. Genotyping algorithms provide a confidence score for each marker call that is currently not integrated in existing methods. There is a need for a model that incorporates this prior information within the standard identical by descent (IBD) and association analyses.
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