ArticleG3 (Bethesda, Md.)2013
Practical considerations regarding the use of genotype and pedigree data to model relatedness in the context of genome-wide association studies.
Article in G3 (Bethesda, Md.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
47 citing papers in PubMed.
- Genome-wide association study of cocaine self-administration behavior in Heterogeneous Stock rats.Nature communications · 2026Article
- Novel candidate genes for vestibular function identified through GWAS in the hybrid mouse diversity panel.BMC genomics · 2026Article
- Fruit weight regulation by a paralog of Cell Size Regulator (CSR) in tomato and other crops.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Genetic architecture and mechanisms of host-microbiome interactions from a multi-cohort analysis of outbred laboratory rats.Nature communications · 2025Article
- Forward and reverse genomic screens enhance the understanding of phenotypic variation in a large Chinese rhesus macaque cohort.Nature communications · 2025Article
- Novel insights into the genetic architecture and mechanisms of host/microbiome interactions from a multi-cohort analysis of outbred laboratory rats.bioRxiv : the preprint server for biology · 2025Article
- Genome-Wide Association Study of Age-Related Hearing Loss in CFW Mice Identifies Multiple Genes and Loci, Including Prkag2.Journal of the Association for Research in Otolaryngology : JARO · 2025Article
- Genetic Loci Influencing Cue-Reactivity in Heterogeneous Stock Rats.Genes, brain, and behavior · 2025Article
- Immunological roads diverged: mapping tuberculosis outcomes in mice.Trends in microbiology · 2025Review
- PAGER: A novel genotype encoding strategy for modeling deviations from additivity in complex trait association studies.BioData mining · 2024Article
- Genome-wide association study of delay discounting in Heterogeneous Stock rats.Genes, brain, and behavior · 2024Article
- Genomic Loci Influencing Cue-Reactivity in Heterogeneous Stock Rats.bioRxiv : the preprint server for biology · 2024Article
- Genome-wide association study of delay discounting in Heterogenous Stock rats.bioRxiv : the preprint server for biology · 2023Article
- Identification of novel sources of partial and incomplete hypersensitive resistance to rust and associated genomic regions in common bean.BMC plant biology · 2023Article
- Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks.Cell reports · 2023Article
- Article
- Which mouse multiparental population is right for your study? The Collaborative Cross inbred strains, their F1 hybrids, or the Diversity Outbred population.G3 (Bethesda, Md.) · 2023Article
- Impact of diet and host genetics on the murine intestinal mycobiome.Nature communications · 2023Article
- Evaluating the power and limitations of genome-wide association studies in Caenorhabditis elegans.G3 (Bethesda, Md.) · 2022Article
- Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population.Alcoholism, clinical and experimental research · 2022Article
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4 authors.
Funding
Abstract
Genome-wide association studies of complex traits often are complicated by relatedness among individuals. Ignoring or inappropriately accounting for relatedness often results in inflated type I error rates. Either genotype or pedigree data can be used to estimate relatedness for use in mixed-models when undertaking quantitative trait locus mapping. We performed simulations to investigate methods for controlling type I error and optimizing power considering both full and partial pedigrees and, similarly, both sparse and dense marker coverage; we also examined real data sets. (1) When marker density was low, estimating relatedness by genotype data alone failed to control the type I error rate; (2) this was resolved by combining both genotype and pedigree data. (3) When sufficiently dense marker data were used to estimate relatedness, type I error was well controlled and power increased; however, (4) this was only true when the relatedness was estimated using genotype data that excluded genotypes on the chromosome currently being scanned for a quantitative trait locus.
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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.