Multiple Hypothesis Testing in a Genome Wide Association Study of Bovine Tuberculosis

Genom tabanlı ilişki çalışmaları (GTİÇ) kullanılarak çiftlik hayvanlarının verimleri ile ilişkili tekil nükleotid polymorfizmler (TNP) belirlenebilmektedir. GTİÇ'den elde edilecek sonuçlar hem fenotip hem de genotip veri setlerinin kalitesine bağlı olacaktır. Populasyon tabakası, çoklu hipotez düzeltim yöntemleri ve kalite kontol süreçleri yanlış pozitif (veya negatif) ilişki sonuçlarına yol açabilir. Bu çalışmanın amaçları: bir sığır tüberküloz GTİÇ veri setine 1) değişik kalite ölçütleri ve çoklu hipotez düzeltme yöntemlerinin 2) bazı TNP regresyon yöntemleri ile atasal tabakaların belirlenmesi ve düzeltilmesinin etkilerinin incelenmesidir. Çoklu hipotez düzeltmesi olmadan TNP regresyon modeli ile 2, 7, 8 ve 13. kromozomdan önemli TNP'ler (P

Sığır Tüberkülozu İçin Çoklu Hipotez Düzeltmesi İle Genom Tabanlı İlişki Analizi

Genome-wide association studies (GWAS) have been used to detect single nucleotide polymorphisms (SNPs) related to various animal traits. The outcome of GWAS is based on quality of the both phenotypic and genotypic datasets. False positive (or negative) associations can be obtained due to multiple hypothesis testing procedures, quality control measures, or an undetected population structure. The objectives of this study were to 1) investigate different multiple hypothesis testing procedures with different quality measures and 2) to detect and correct ancestral stratification using different single SNPs models of the bovine tuberculosis GWA data set. Based on a regression model, SNPs from chromosomes 2, 7, 8 and 13 were detected at a significance level of P<0.001 without correction for multiple hypothesis testing. However, after Bonferroni correction, Hochberg's method and permutation test for multiple hypothesis correction genomic signals, it became non-significant. Only a false discovery rate approach detected weak signals (at level of 0.54) from chromosomes 2, 8, and 13. We used a model that took into account the effect of linkage disequilibrium to the multiple hypothesis testing procedures by combining adjacent SNPs test statistics with windows sizes of 2, 4 and 6. We detected strong genomic signals from chromosomes 13, 8, 6 and 2 at windows size 6. The results of this study showed that multiple hypothesis testing procedures are related to false positive genomic signals. It is difficult to suggest universally acceptable multiple hypothesis testing and QC measures and their thresholds due to sources of variations between species and within populations. However, additional analytical approaches and studies are needed to evaluate the effects of linkage disequilibrium on the multiple hypothesis testing procedures and QC measures (especially for minor allele frequencies) to GWAS under various scenarios including, but not limited to, level of heritability, linkage disequilibrium, population structure, and population size.

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