Comparison of the statistical methods for genome-wide association studies on simulated quantitative traits of domesticated goats (Capra hircus L.)

Cebeci Z., Bayraktar M., Gökçe G.

SMALL RUMINANT RESEARCH, cilt.227, sa.2023, ss.1-12, 2023 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 227 Sayı: 2023
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1016/j.smallrumres.2023.107053
  • Dergi Adı: SMALL RUMINANT RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.1-12
  • Çukurova Üniversitesi Adresli: Evet

Özet

Genome-wide association studies (GWAS) are one of the essential methods used to find associations between phenotypes and genes. The main problem in GWAS methods is false positives that occur from family relationships and population structure. In this study, the performances and powers of traditional and state-of-the-art statistical methods used in genome-wide association studies were compared on nine simulated quantitative traits using genotypic data of the domesticated goats (Capra hircus L.). The traits were simulated with varying degrees of heritability from 0.05 to 0.8. The findings revealed that Blink and FarmCPU are the outperforming methods to control false positives more efficiently for the medium and high heritability traits. At the same time, Blink promises to identify true positive signals more efficiently for the low heritability traits. The other multi-loci statistical methods SUPER and MLMM perform worse than Blink and FarmCPU but better than all of the single-locus methods GLM, MLM, CMLM and ECLMM. Additionally, Bonferroni or Holm's adjustment procedures were better in multiple testing of associations at the 1 % significance level to get more accurate results for the high heritability traits.