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the claim
Conditional analysis of a SNP in a GWAS accounts for secondary association signals
the verdict
SUPPORTED
the evidence backs this
refutedsupported
the weight of evidence
4 sources for · 0 against

Conditional analysis of single nucleotide polymorphisms (SNPs) in genome-wide association studies (GWAS) is a well-established and successful method used to account for and identify secondary association signals.

Evidence for · 4
Colocalization of GWAS and eQTL signals at loci with multiple signals identifies additional candidate genes for body fat distribution.
2019 · cited by 51
The study explicitly used conditional analysis to identify conditionally distinct or secondary eQTL signals at multi-signal GWAS loci.
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The analysis

The claim states that conditional analysis of a SNP in a GWAS accounts for secondary association signals. Papers [2], [3], [5], and [9] all explicitly utilize or discuss conditional analysis as the primary method to detect, distinguish, and account for secondary/independent association signals at GWAS loci. Therefore, the evidence overwhelmingly supports the claim, resulting in a 'SUPPORTED' verdict.

More for · 3
A mega-analysis of expression quantitative trait loci in retinal tissue
2020 · cited by 38
A conditional analysis was utilized to reveal 744 independent secondary eQTL signals for 3,007 eGenes.
GWAS of the electrocardiographic QT interval in Hispanics/Latinos generalizes previously identified loci and identifies population-specific signals
2017 · cited by 24
Conditional analyses were applied to distinguish six secondary signals across multiple loci like NOS1AP and ATP1B1.
Assessment of significance of conditionally independent GWAS signals
2021 · cited by 3
The paper notes that conditional analysis has been successful in identifying secondary signals among multiple independently associated SNPs within an LD region.
Everything we examined (12)
  1. From GWAS to Gene: Transcriptome-Wide Association Studies and Other Methods to Functionally Understand GWAS Discoveriespeer-reviewedno side takennot shown: read and judged not to bear on this claim
  2. Improved analyses of GWAS summary statistics by reducing data heterogeneity and errorspeer-reviewedno side takennot shown: read and judged not to bear on this claim
  3. Colocalization of GWAS and eQTL signals at loci with multiple signals identifies additional candidate genes for body fat distribution.peer-reviewedsupports
  4. A mega-analysis of expression quantitative trait loci in retinal tissuepeer-reviewedsupports
  5. Comprehensive Multiple eQTL Detection and Its Application to GWAS Interpretationpeer-reviewedno side takennot shown: read and judged not to bear on this claim
  6. GWAS of the electrocardiographic QT interval in Hispanics/Latinos generalizes previously identified loci and identifies population-specific signalspeer-reviewedsupports
  7. Improved Use of Small Reference Panels for Conditional and Joint Analysis with GWAS Summary Statisticspeer-reviewedno side takennot shown: read and judged not to bear on this claim
  8. Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattlepeer-reviewedno side takennot shown: read and judged not to bear on this claim
  9. Single Nucleotide Polymorphism Mapping Using Genome-Wide Unique Sequencespeer-reviewedno side takennot shown: read and judged not to bear on this claim
  10. Assessment of significance of conditionally independent GWAS signalspeer-reviewedsupports
  11. Genome-wide association analysis using multiple Atlantic salmon populationspeer-reviewedno side takennot shown: read and judged not to bear on this claim
  12. Identifying expression and DNA methylation biomarkers for lung adenocarcinoma risk in East Asia.peer-reviewedno side takennot shown: read and judged not to bear on this claim
The paper trail · every fact has a biography
first checked05 Aug 2026
judged → SUPPORTED · 8605 Aug 2026
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