ArticleInternational journal of molecular sciences2026
CQD: A Rapid and Accurate Tool for Identifying High-Confidence QTLs and Candidate Genes from GWAS Summary Statistics.
Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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
1 citing paper in PubMed.
- Phenotypic variation and genetic architecture of seedling salt tolerance in Xinjiang wheat revealed by GWAS and resequencing.Frontiers in plant science · 2026Article
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11 authors.
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Abstract
Genome-wide association studies (GWAS) are a powerful approach for elucidating the genetic architecture of complex traits. The widespread application of GWAS across diverse crop species has generated vast amounts of GWAS summary statistics, creating a pressing need for effective tools to identify high-confidence quantitative trait loci (QTLs) from these data. Here, we present Candidate QTL Detector (CQD), a tool that enables the rapid and accurate identification of confident QTL regions from GWAS summary statistics. To evaluate the performance of CQD, we reanalyzed 64 phenotypic traits from a previously published maize diversity panel. CQD identified 108 high-confidence QTLs from 4179 significant GWAS signals, and these QTLs harbored several well-characterized genes, including
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