Integrating External Controls by Regression Calibration for Genome-Wide Association Study.
Genes (Basel)
; 15(1)2024 01 03.
Article
in En
| MEDLINE
| ID: mdl-38254957
ABSTRACT
Genome-wide association studies (GWAS) have successfully revealed many disease-associated genetic variants. For a case-control study, the adequate power of an association test can be achieved with a large sample size, although genotyping large samples is expensive. A cost-effective strategy to boost power is to integrate external control samples with publicly available genotyped data. However, the naive integration of external controls may inflate the type I error rates if ignoring the systematic differences (batch effect) between studies, such as the differences in sequencing platforms, genotype-calling procedures, population stratification, and so forth. To account for the batch effect, we propose an approach by integrating External Controls into the Association Test by Regression Calibration (iECAT-RC) in case-control association studies. Extensive simulation studies show that iECAT-RC not only can control type I error rates but also can boost statistical power in all models. We also apply iECAT-RC to the UK Biobank data for M72 Fibroblastic disorders by considering genotype calling as the batch effect. Four SNPs associated with fibroblastic disorders have been detected by iECAT-RC and the other two comparison methods, iECAT-Score and Internal. However, our method has a higher probability of identifying these significant SNPs in the scenario of an unbalanced case-control association study.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Genome-Wide Association Study
Type of study:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
Genes (Basel)
Year:
2024
Document type:
Article