fgwas protocols

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fgwas specifications


Unique identifier OMICS_11295
Name fgwas
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
License GNU General Public License version 2.0
Computer skills Advanced
Version 0.3.6
Stability Stable
GNU Scientific, Boost
Maintained Yes


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  • person_outline Joseph Pickrell <>

Publication for fgwas

fgwas in pipelines

PMCID: 4572002
PMID: 26157023
DOI: 10.1093/hmg/ddv260

[…] basis of these associations in terms of disease pathology and ultimately identify causal genes. these data can be combined with statistical fine-mapping in multiple ways. several approaches, such as fgwas (), use functional annotations as priors for potential causal variants. the paintor method () described above can perform similar re-weighting in analysis of summary statistics. this approach […]

PMCID: 4580981
PMID: 26394269
DOI: 10.1038/ncomms9019

[…] to mitigate overfitting (similar to the procedure performed by pickrell) on these 75 annotations to identify a final best-fitting model that included 6 annotations. annotation information used by fgwas was derived from a variety of sources including maurano et al., thurman et al. and hffman et al. (see appendix of pickrell for details)., using summary results from the gwma (effect size, […]

PMCID: 4580981
PMID: 26394269
DOI: 10.1038/ncomms9019

[…] or epigenetic roles within pbc risk loci, more direct biological experimental approaches are required to pinpoint the disease-causal variants at these loci., we also applied functional gwas (fgwas) and its associated annotation file to our full set of discovery gwma results and thereby identified 75 annotations with enrichment (p<0.01 from fgwas) of gwma association signals (). […]

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fgwas in publications

PMCID: 5828664
PMID: 29412141
DOI: 10.7554/eLife.31977.047

[…] as distinct islet enhancer subclasses., to understand the relationship of these various state definitions to genetic variants influencing t2d risk, we applied the hierarchical modelling approach fgwas () to the same sets of large-scale gwas data for t2d (from diagram []) and fg (engage []) described in section 2.1. fgwas allowed us to combine gwas and genomic data to determine […]

PMCID: 5704019
PMID: 29180722
DOI: 10.1038/s41598-017-16550-8

[…] in second stage analyses, we annotated all variants discovered in the hutterites using 25 sequence-based annotations and 332 functional annotations (see methods) and applied the functional gwas (fgwas) framework to further evaluate the gwas results and prioritize candidate rare variants based on prior functional knowledge. we split the genome into blocks averaging 125kb (~50 revs) […]

PMCID: 5691156
PMID: 29147026
DOI: 10.1038/s41598-017-15705-x

[…]  ) where gene names for those loci were also shown, except intergenic snps. interestingly, several significant loci with stronger signals were distributed on chromosomes 14 and 18.figure 2 , applying fgwas to our putamen gwas summary statistics data, only one snp was prominent at posterior probability > 0.5, two snps (in the same ld block) at posterior probability > 0.4, nine snps (in four l […]

PMCID: 5938138
PMID: 29112194
DOI: 10.1038/mp.2017.200

[…] consent and protocols were approved by the institutional review boards overseeing the individual studies (see )., summary statistics from european ancestry subjects in cats, coga-ccgwas, coga-fgwas, ozalc+ and sage were combined to form the discovery analysis. replication analyses were conducted in the yale-penn () sample which was the major dataset contributing to the prior study […]

PMCID: 5559603
PMID: 28814792
DOI: 10.1038/s41467-017-00366-1

[…] (fig. , supplementary fig. ) and genes with a ceqtl showed go enrichment predominantly in metabolic processes (supplementary fig. ). functional annotation enrichment and fine mapping analyses by fgwas revealed that reqtls were more enriched in promoter-flanking regions, ctcf binding sites and enhancer regions, while constant eqtls were more common in promoter regions, 3′ and 5′ untranslated […]

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fgwas institution(s)
New York Genome Center, New York, NY, USA; Department of Biological Sciences, Columbia University, New York, NY, USA

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