التفاصيل البيبلوغرافية
| العنوان: |
Better together against genetic heterogeneity: A sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank |
| المؤلفون: |
Lin, Boxi, Paterson, Andrew D., Sun, Lei |
| المساهمون: |
Cordell, Heather J, Natural Sciences and Engineering Research Council of Canada, University of Toronto Data Science Institute |
| المصدر: |
PLOS Genetics ; volume 20, issue 4, page e1011221 ; ISSN 1553-7404 |
| بيانات النشر: |
Public Library of Science (PLoS) |
| سنة النشر: |
2024 |
| المجموعة: |
PLOS Publications (via CrossRef) |
| الوصف: |
Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP’s main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| DOI: |
10.1371/journal.pgen.1011221 |
| الإتاحة: |
https://doi.org/10.1371/journal.pgen.1011221Test |
| حقوق: |
http://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: |
edsbas.E7705050 |
| قاعدة البيانات: |
BASE |
