| Title: | Integrating External Controls by Regression Calibration for Genome-Wide Association Study |
| Journal: | Genes |
| Published: | 3 Jan 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38254957/ |
| DOI: | https://doi.org/10.3390/genes15010067 |
| URL: | https://www.mdpi.com/2073-4425/15/1/67/pdf?version=1704261554 |
Publication 9009
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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.</p>
5 Authors
- Lirong Zhu
- Shijia Yan
- Xuewei Cao
- Shuanglin Zhang
- Qiuying Sha
1 Application
| Application ID | Title |
|---|---|
| 102999 | Constructing genotype and phenotype network helps reveal phenome-wide association studies in biobanks |
Enabling scientific discoveries that improve human health