ArticleGenetic epidemiology2016
Small Sample Kernel Association Tests for Human Genetic and Microbiome Association Studies.
Article in Genetic epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Trial
- Multi-marker testing based on accelerated failure time models under possible left truncation and competing risks.Briefings in bioinformatics · 2026Article
- "Microbial and immune modulation by 2'-fucosyllactose supplementation during gestation: a strategy to prevent food allergies".Gut microbes · 2025Article
- Oligogenic risk score for Gilles de la Tourette syndrome reveals a genetic continuum of tic disorders.Journal of applied genetics · 2025Article
- cytoKernel: robust kernel embeddings for assessing differential expression of single-cell data.Bioinformatics (Oxford, England) · 2025Article
- JASPER: Fast, powerful, multitrait association testing in structured samples gives insight on pleiotropy in gene expression.American journal of human genetics · 2024Article
- JASPER: fast, powerful, multitrait association testing in structured samples gives insight on pleiotropy in gene expression.bioRxiv : the preprint server for biology · 2023Article
- FiMAP: A fast identity-by-descent mapping test for biobank-scale cohorts.PLoS genetics · 2023Article
- Excalibur: A new ensemble method based on an optimal combination of aggregation tests for rare-variant association testing for sequencing data.PLoS computational biology · 2023Article
- A maximum kernel-based association test to detect the pleiotropic genetic effects on multiple phenotypes.Bioinformatics (Oxford, England) · 2023Article
- MATS: a novel multi-ancestry transcriptome-wide association study to account for heterogeneity in the effects of cis-regulated gene expression on complex traits.Human molecular genetics · 2023Article
- Phylogeny-guided microbiome OTU-specific association test (POST).Microbiome · 2022Article
- Testing microbiome association using integrated quantile regression models.Bioinformatics (Oxford, England) · 2022Article
- Intestinal Flora-Derived Kynurenic Acid Protects Against Intestinal Damage Caused byFrontiers in microbiology · 2022Article
- MiRKAT-MC: A Distance-Based Microbiome Kernel Association Test With Multi-Categorical Outcomes.Frontiers in genetics · 2022Article
- Sufficient dimension reduction for compositional data.Biostatistics (Oxford, England) · 2021Article
- PaIRKAT: A pathway integrated regression-based kernel association test with applications to metabolomics and COPD phenotypes.PLoS computational biology · 2021Article
- Variant-set association test for generalized linear mixed model.Genetic epidemiology · 2021Article
- Testing and controlling for horizontal pleiotropy with probabilistic Mendelian randomization in transcriptome-wide association studies.Nature communications · 2020Article
- Association test using Copy Number Profile Curves (CONCUR) enhances power in rare copy number variant analysis.PLoS computational biology · 2020Article
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Authors and funding
5 authors.
Funding
Abstract
Kernel machine based association tests (KAT) have been increasingly used in testing the association between an outcome and a set of biological measurements due to its power to combine multiple weak signals of complex relationship with the outcome through the specification of a relevant kernel. Human genetic and microbiome association studies are two important applications of KAT. However, the classic KAT framework relies on large sample theory, and conservativeness has been observed for small sample studies, especially for microbiome association studies. The common approach for addressing the small sample problem relies on computationally intensive resampling methods. Here, we derive an exact test for KAT with continuous traits, which resolve the small sample conservatism of KAT without the need for resampling. The exact test has significantly improved power to detect association for microbiome studies. For binary traits, we propose a similar approximate test, and we show that the approximate test is very powerful for a wide range of kernels including common variant- and microbiome-based kernels, and the approximate test controls the type I error well for these kernels. In contrast, the sequence kernel association tests have slightly inflated genomic inflation factors after small sample adjustment. Extensive simulations and application to a real microbiome association study are used to demonstrate the utility of our method.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.