Detecting autozygosity through runs of homozygosity: A comparison of three autozygosity detection algorithms

摘要: A central aim for studying runs of homozygosity (ROHs) in genome-wide SNP data is to detect the effects autozygosity (stretches two homologous chromosomes within same individual that are identical by descent) on phenotypes. However, it unknown which current ROH detection program, and set parameters a given optimal differentiating ROHs truly autozygous from homozygous at marker level but vary unmeasured variants between markers. We simulated 120 Mb sequence order know true state autozygosity. then extracted common this mimic properties platforms performed analyses using three popular programs, PLINK, GERMLINE, BEAGLE. varied thresholds each program (e.g., prior probabilities, lengths ROHs) understand their detecting known Within PLINK outperformed GERMLINE BEAGLE distant ancestors. PLINK's sliding window algorithm worked best when pruned linkage disequilibrium (LD). Our results provide both general specific recommendations maximizing data, should apply equally well research whole-genome burden or whether regions predictive association mapping methods.