ArticleFrontiers in genetics2022
Evaluation and characterization of expression quantitative trait analysis methods in the Hybrid Rat Diversity Panel.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Sry-modified laboratory rat lines to study sex-chromosome effects underlying sex differences in physiology and disease: Four Core Genotypes and more.Biology of sex differences · 2026Article
- Hi-C sequencing data from frontal cortex of laboratory rats.Scientific data · 2025Article
- Modeling Pain Without Injury: Inherited Rodent Models as Mechanistic Windows into Chronic Pain.Function (Oxford, England) · 2025Review
- The SHR/Akr Y chromosome reveals repeated turnover of the rat pseudoautosomal region.bioRxiv : the preprint server for biology · 2025Article
- Genome-wide profiling and functional characterization of circular RNAs in neural development and injury: insights from a rat model research.Cellular and molecular life sciences : CMLS · 2025Article
- Establishing the hybrid rat diversity program: a resource for dissecting complex traits.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Pangenome reconstruction in rats enhances genotype-phenotype mapping and variant discovery.iScience · 2025Article
- A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats.Cell genomics · 2024Article
- A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats.bioRxiv : the preprint server for biology · 2023Article
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6 authors.
Funding
Abstract
The Hybrid Rat Diversity Panel (HRDP) is a stable and well-characterized set of more than 90 inbred rat strains that can be leveraged for systems genetics approaches to understanding the genetic and genomic variation associated with complex disease. The HRDP exhibits substantial between-strain diversity while retaining substantial within-strain isogenicity, allowing for the precise mapping of genetic variation associated with complex phenotypes and providing statistical power to identify associated variants. In order to robustly identify associated genetic variants, it is important to account for the population structure induced by inbreeding. To this end, we investigate the performance of four plausible approaches towards modeling quantitative traits in the HRDP and quantify their operating characteristics. In particular, we investigate three approaches based on genome-wide mixed model analysis, and one approach based on ordinary least squares linear regression. Towards facilitating study planning and design, we conduct extensive simulations to investigate the power of genetic association analyses in the HRDP, and characterize the impressive attained power. In simulation of eQTL data in the HRDP, we find that a mixed model approach that leverages leave-one-chromosome-out kinship estimation attains the highest power while controlling type I error.
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