LocusFocus: A web-based colocalization tool for the annotation and functional follow-up of GWAS

Panjwani, Naim; Wang, Fan; Wang, Cheng; He, Gengming; Mastromatteo, Scott; Bao, Allen; Gong, Jiafen; Rommens, Johanna M.; Sun, Lei; Strug, Lisa J.

doi:10.1101/2020.01.02.891291

Cited by 3 publications

(5 citation statements)

References 27 publications

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“… 60 This will be addressed in future work. SS2 is implemented in a web-based colocalization tool, LocusFocus, 25 which enables integration of GWAS summary statistics with any secondary SNP-level dataset by using p values and LD for the region of interest. The eQTL summary statistics from GTEx are made available for selection within the web server to test colocalization with tissues and genes from GTEx.…”

Section: Discussionmentioning

confidence: 99%

“…The SS2 framework as delineated here does not integrate summary statistics from greater than two studies, although there would be value in colocalizing GWAS summary data with multiple molecular phenotypes and multiple GWAS traits simultaneously as proposed in Giambartolomei et al 60 This will be addressed in future work. SS2 is implemented in a web-based colocalization tool, LocusFocus, 25 which enables integration of GWAS summary statistics with any secondary SNP-level dataset by using p values and LD for the region of interest. The eQTL summary statistics from GTEx are made available for selection within the web server to test colocalization with tissues and genes from GTEx.…”

Section: A B D Cmentioning

confidence: 99%

“…The SS2 has been implemented in the application LocusFocus. 25 For method comparison, we choose COLOC and CO-LOC2 from the class of Bayesian methods, and SMR and SMR-multi from the class of frequentist methods. Among the three Bayesian approaches that consider the issue of the composite null hypothesis (COLOC, GWAS-PW, and COLOC2), COLOC has been shown to have better performance than GWAS-PW when a single causal variant is shared between the two studies, 15 while GWAS-PW can have better performance when eQTL and GWAS causal variants are distinct.…”

Section: Introductionmentioning

confidence: 99%

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A flexible summary statistics-based colocalization method with application to the mucin cystic fibrosis lung disease modifier locus

Wang

Panjwani

Wang

et al. 2022

The American Journal of Human Genetics

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Section: Discussionmentioning

confidence: 99%

Section: A B D Cmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A flexible summary statistics-based colocalization method with application to the mucin cystic fibrosis lung disease modifier locus

Wang

Panjwani

Wang

et al. 2022

The American Journal of Human Genetics

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“…Similarly, the SS2 could assess colocalization using any SNP-level data including DNA methylation (meQTLs), protein QTLs (pQTLs) or metabolites (metQTLs). SS2 is implemented in a web-based colocalization tool, LocusFocus 21 which enables integration of GWAS summary statistics with any secondary SNP-level dataset by using p-values and LD for the region of interest. The eQTL summary statistics from GTEx are made available for selection within the web server to test colocalization with tissues and genes from GTEx.…”

Section: Discussionmentioning

confidence: 99%

“…The SS2 has been implemented in the application LocusFocus. 21 For method comparison, we choose COLOC and COLOC2 from the class of Bayesian methods, and SMR and SMR-multi from the class of frequentist methods. Among the three Bayesian approaches that consider the issue of the composite null hypothesis (COLOC, GWAS-PW and COLOC2), COLOC has been shown to have better performance than GWAS-PW when a single causal variant is shared between the two studies, 15 while GWAS-PW can have better performance when the two causal variants are distinct.…”

Section: Introductionmentioning

confidence: 99%

A flexible summary-based colocalization method with application to the mucin Cystic Fibrosis lung disease modifier locus

Wang

Panjwani

Wang

et al. 2021

Preprint

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Mucus obstruction is a central feature in the Cystic Fibrosis (CF) airways. A genome-wide association study (GWAS) of lung disease by the CF Gene Modifier Consortium (CFGMC) identified a significant locus containing two mucin genes, MUC20 and MUC4. Expression quantitative trait locus (eQTL) analysis using human nasal epithelial (HNE) from 94 CF Canadians in the CFGMC demonstrated MUC4 eQTLs that mirrored the lung association pattern in the region, suggesting that MUC4 expression may mediate CF lung disease. Complications arose, however, with colocalization testing using existing methods: the locus is complex and the associated SNPs span a 0.2Mb region with high linkage disequilibrium and evidence of eQTLs for multiple genes and tissues (heterogeneity). We previously developed the Simple Sum (SS), a powerful colocalization test in regions with heterogeneity, but SS assumed eQTLs to be present to achieve type I error control. Here we propose a two-stage SS (SS2) colocalization test that avoids a prior eQTL assumptions, accounts for multiple hypothesis testing and the composite null hypothesis and enables meta-analysis. We compare SS2 to published approaches through simulation and demonstrate type I error control for all settings with the greatest power in the presence of high LD and heterogeneity. Applying SS2 to the MUC20/MUC4 CF lung disease locus with eQTLs from CF HNE revealed significant colocalization with MUC4 (p = 1.71×10-5) rather than MUC20. The SS2 is a powerful method to inform the responsible gene(s) at a locus and guide future functional studies. SS2 has been implemented in the application LocusFocus (locusfocus.research.sickkids.ca).

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Genome-Wide Association Analysis and Genomic Prediction of Thyroglobulin Plasma Levels

Pleić

Leko

Gunjača

et al. 2022

IJMS

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Thyroglobulin (Tg) is an iodoglycoprotein produced by thyroid follicular cells which acts as an essential substrate for thyroid hormone synthesis. To date, only one genome-wide association study (GWAS) of plasma Tg levels has been performed by our research group. Utilizing recent advancements in computation and modeling, we apply a Bayesian approach to the probabilistic inference of the genetic architecture of Tg. We fitted a Bayesian sparse linear mixed model (BSLMM) and a frequentist linear mixed model (LMM) of 7,289,083 variants in 1096 healthy European-ancestry participants of the Croatian Biobank. Meta-analysis with two independent cohorts (total n = 2109) identified 83 genome-wide significant single nucleotide polymorphisms (SNPs) within the ST6GAL1 gene (p<5×10−8). BSLMM revealed additional association signals on chromosomes 1, 8, 10, and 14. For ST6GAL1 and the newly uncovered genes, we provide physiological and pathophysiological explanations of how their expression could be associated with variations in plasma Tg levels. We found that the SNP-heritability of Tg is 17% and that 52% of this variation is due to a small number of 16 variants that have a major effect on Tg levels. Our results suggest that the genetic architecture of plasma Tg is not polygenic, but influenced by a few genes with major effects.

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LocusFocus: A web-based colocalization tool for the annotation and functional follow-up of GWAS

Cited by 3 publications

References 27 publications

A flexible summary statistics-based colocalization method with application to the mucin cystic fibrosis lung disease modifier locus

A flexible summary statistics-based colocalization method with application to the mucin cystic fibrosis lung disease modifier locus

A flexible summary-based colocalization method with application to the mucin Cystic Fibrosis lung disease modifier locus

Genome-Wide Association Analysis and Genomic Prediction of Thyroglobulin Plasma Levels

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