Nov 4, 2018

Fast and accurate shared segment detection and relatedness estimation in un-phased genetic data using TRUFFLE

BioRxiv : the Preprint Server for Biology
Apostolos DimitromanolakisLei Sun

Abstract

Relationship estimation and segment detection between individuals is an important aspect of disease gene mapping. Existing methods are either tailored for computational efficiency, or require phasing to improve accuracy. We developed TRUFFLE, a method that integrates computational techniques and statistical principles for the identification and visualization of identity-by-descent (IBD) segments using un-phased data. By skipping the haplotype phasing step and, instead, relying on a simpler region-based approach, our method is computationally efficient while maintaining inferential accuracy. In addition, an error model corrects for segment break-ups that occur as a consequence of genotyping errors. TRUFFLE can estimate relatedness for 3.1 million pairs from the 1000 Genomes Project data in a few minutes on a typical laptop computer. Consistent with expectation, we identified three second cousin or closer pairs across different populations, while commonly used methods identified over 15,000 such pairs. Similarly, within populations, we identified much fewer related pairs. Benchmarking to methods relying on phased data, TRUFFLE has a favorable accuracy profile but is drastically faster. We also identified specific local genomic re...Continue Reading

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Mentioned in this Paper

Genome
Genetic Pedigree
Gene Type
Genomics
Genus Tuber (fungus)
Inflammatory Bowel Diseases
Local
Genotype Determination
Population Group
Computer, BLOOD-PRESSURE

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