Evidence map›Paper›PMID 41203876›Full record

ArticleHeredity2026

GWAS SVatalog: a visualization tool to aid fine-mapping of GWAS loci with structural variations.

Shalvi Chirmade, Zhuozhi Wang, Scott Mastromatteo, Eric Sanders, Bhooma Thiruvahindrapuram, Thomas Nalpathamkalam, Giovanna Pellecchia, Fan Lin, Katherine Keenan, Rohan V Patel and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heredity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Shalvi ChirmadeProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.ORCID 0009-0002-2015-6718
Zhuozhi WangProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Scott MastromatteoProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Eric SandersProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Bhooma ThiruvahindrapuramProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.ORCID 0000-0003-1128-008X
Thomas NalpathamkalamProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Giovanna PellecchiaProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Fan LinProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Katherine KeenanProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Rohan V PatelProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.ORCID 0000-0001-8674-9706
Wilson Wl SungDepartment of Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada.
Delnaz RoshandelProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Joe WhitneyProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Sana AllanaProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Julie AvolioTranslational Medicine, The Hospital for Sick Children, Toronto, ON, Canada.
Paul Dw EckfordCystic Fibrosis Canada, Toronto, ON, Canada.
Felix RatjenTranslational Medicine, The Hospital for Sick Children, Toronto, ON, Canada.
Lisa J StrugProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada. lisa.strug@utoronto.ca.ORCID 0000-0003-0503-9740

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have been successful in identifying single nucleotide polymorphisms (SNPs) associated with phenotypic traits. However, SNPs form an incomplete set of variation across the genome and since a large percentage of GWAS-significant SNPs lie in non-coding regions, their impact on a given trait is difficult to decipher. Recognizing whether these SNPs are tagging other polymorphisms, like structural variations (SV), is an important step towards understanding the putative causal variation at GWAS loci. Here, we develop GWAS SVatalog ( https://svatalog.research.sickkids.ca/ ), a novel open-source web tool that computes and visualizes linkage disequilibrium (LD) between SVs and GWAS-associated SNPs throughout the human genome. The tool combines GWAS Catalog's SNP-trait association data across 14,479 phenotypes with LD statistics calculated between 35,732 SVs and 116,870 SNPs identified in 101 whole-genome long-read sequences. We show that different SV types are more likely to overlap regulatory features, and that SVs less directly tagged by GWAS-associated SNPs more frequently overlap CpG islands and promoters. We use GWAS SVatalog to identify SVs that may explain GWAS loci for iron levels, refractive error, and Alzheimer's disease, where previously SNPs were unable to provide a causal explanation. GWAS SVatalog advances the fine-mapping of GWAS loci with structural variations, enabling researchers to associate 35,732 common SVs with 14,479 phenotypes, accelerating the understanding of disease etiology.

Indexed as

Chromosome MappingGenome-Wide Association StudyGenomic Structural VariationSoftwareGenome, HumanHumansLinkage DisequilibriumPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID41203876
PMCPMC13031531

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LicenceCC BY
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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.