Genomic summary statistics and meta-analysis for set-based gene-environment interaction tests in large-scale sequencing studies
Wang, X.; Pham, D. T.; Westerman, K. E.; Pan, C.; Manning, A. K.; Chen, H.
Show abstract
We propose an efficient method to generate the summary statistics for set-based gene-environment interaction tests, as well as a meta-analysis approach that aggregates the summary statistics across different studies, which can be applied to large biobank-scale sequencing studies with related samples. Simulations showed that meta-analysis is numerically concordant with the equivalent pooled analysis using individual-level data. Moreover, meta-analysis accommodates heterogeneity between studies and enhances power in multi-ethnic studies. We applied the meta-analysis approach to the whole-exome sequencing data from the UK Biobank and successfully identified gene regions associated with waist-hip ratio, as well as those with sex-specific genetic effects.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Evaluation of Bayesian Linear Regression Models for Gene Set Prioritization in Complex Diseases 96%
- Tissue specificity-aware TWAS (TSA-TWAS) framework identifies novel associations with metabolic, immunologic, and virologic traits in HIV-positive adults 95%
- Major sex differences in allele frequencies for X chromosome variants in the 1000 Genomes Project data 95%
Similar papers in this journal
Similar papers in this journal
- Benchmarking Mendelian Randomization methods for causal inference using genome-wide association study summary statistics 95%
- Significance tests for R2 of out-of-sample prediction using polygenic scores 95%
- A method to map and interpret pleiotropic loci using summary statistics of multiple traits 95%
Similar papers in this journal
- BinomiRare: A carriers-only test for association of rare genetic variants with a binary outcome for mixed models and any case-control proportion 96%
- A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically-determined protein-protein networks 96%
- Evaluation of imputation performance of multiple reference panels in a Pakistani population 95%
Similar papers in this journal
- kTWAS: integrating kernel-machine with transcriptome-wide association studies improves statistical power and reveals novel genes 96%
- BayesKAT: Bayesian Optimal Kernel-based Test for genetic association studies reveals joint genetic effects in complex diseases 95%
- xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.