ArticleG3 (Bethesda, Md.)2017
The Beavis Effect in Next-Generation Mapping Panels in
Article in G3 (Bethesda, Md.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed, 58 citations in OpenAlex.
- Development of an open-pollinated genetic mapping framework to facilitate the identification of QTL in apples.The plant genome · 2026Article
- Integrative Principal Component-QTL Mapping Identifies Genetic Modifiers of Tumor and Metabolic Traits inInternational journal of molecular sciences · 2026Article
- Cis-regulatory evolution of Wnt family genes contributes to a morphological difference between silkworm species.PLoS biology · 2026Article
- Two noir juice color-associated markers identified from a 'Chambourcin'-based population demonstrate broad applicability acrossFrontiers in plant science · 2026Article
- Identification of novel major quantitative trait loci associated with selenium and zinc accumulation inFrontiers in plant science · 2026Article
- Cis-regulatory evolution ofbioRxiv : the preprint server for biology · 2025Article
- The rice Trait Development Pipeline: a systematic framework guiding upstream research for impact in breeding, with examples from root biology.Plant and soil · 2025Review
- Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster.G3 (Bethesda, Md.) · 2024Article
- Gene expression variation underlying tissue-specific responses to copper stress inbioRxiv : the preprint server for biology · 2023Article
- Unveiling the Mysteries of Non-Mendelian Heredity in Plant Breeding.Plants (Basel, Switzerland) · 2023Review
- An oligogenic architecture underlying ecological and reproductive divergence in sympatric populations.eLife · 2023Article
- Discovery of malathion resistance QTL in Drosophila melanogaster using a bulked phenotyping approach.G3 (Bethesda, Md.) · 2022Article
- Behavioral phenotypes revealed during reversal learning are linked with novel genetic loci in diversity outbred mice.Addiction neuroscience · 2022Article
- Evaluating the power and limitations of genome-wide association studies in Caenorhabditis elegans.G3 (Bethesda, Md.) · 2022Article
- Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing.Genetics · 2022Article
- Identification of a major QTL and genome-wide epistatic interactions for single vs. paired spikelets in a maize-teosinte FMolecular breeding : new strategies in plant improvement · 2022Article
- Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum Using Multiscale Phenotypes.Frontiers in plant science · 2022Article
- The molecular architecture of Drosophila melanogaster defense against Beauveria bassiana explored through evolve and resequence and quantitative trait locus mapping.G3 (Bethesda, Md.) · 2021Article
- Genetic architecture modulates diet-induced hepatic mRNA and miRNA expression profiles in Diversity Outbred mice.Genetics · 2021Article
- Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
A major goal in the analysis of complex traits is to partition the observed genetic variation in a trait into components due to individual loci and perhaps variants within those loci. However, in both QTL mapping and genetic association studies, the estimated percent variation attributable to a QTL is upwardly biased conditional on it being discovered. This bias was first described in two-way QTL mapping experiments by William Beavis, and has been referred to extensively as "the Beavis effect." The Beavis effect is likely to occur in multiparent population (MPP) panels as well as collections of sequenced lines used for genome-wide association studies (GWAS). However, the strength of the Beavis effect is unknown-and often implicitly assumed to be negligible-when "hits" are obtained from an association panel consisting of hundreds of inbred lines tested across millions of SNPs, or in multiparent mapping populations where mapping involves fitting a complex statistical model with several d.f. at thousands of genetic intervals. To estimate the size of the effect in more complex panels, we performed simulations of both biallelic and multiallelic QTL in two major
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What OpenQuestion holds
Registered trials
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.