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Phenome-wide associated studies software tools | Genotype-phenotype interactions

The genome-wide association study (GWAS) is a powerful approach for studying the genetic complexities of human disease. Unfortunately, GWASs often fail to identify clinically significant associations and describing function can be a challenge. GWAS is a phenotype-to-genotype approach. It is now possible to conduct a converse genotype-to-phenotype approach using extensive electronic medical records to define a phenome. This approach associates a single genetic variant with many phenotypes across the phenome and is called a phenome-wide association study (PheWAS).

Source text:
(Ye et al., 2015) Phenome-wide association studies (PheWASs) for functional variants. Eur J Hum Genet.

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PheWAS / Phenome-wide association study
Tests associations between a genetic variant or clinical factor of interest and a compendium of clinical outcomes or phenotypes. PheWAS finds disease-gene associations using ICD9 billing codes. It can serve to construct hypotheses around a variety of exposures. This tool implements a propensity score (PS) method for PS matching or PS adjustment. It employs a penalized maximum likelihood (PML) in logistic regression that can reduce bias in the parameter estimates.
fSNPd / functional SNP allele discovery
Determines genetic components of clinically important disorders. fSNPd relies upon single nucleotide polymorphisms (SNPs). It requires an environmental trigger to occur, like severe drug reactions, pain syndromes occurring after an injury, and susceptibility to infection. It is designed to detect complex genetic causes: environmental triggers that may be multiple and involve age, sex and disease state; phenotype penetrance may be, and multiple independently-penetrant SNP alleles could each cause a clinically indistinguishable phenotype.
An interactive analytics software platform that 1) automates the execution of principled machine learning methods that detect genome- and phenome-wide associations among genotypes, gene expression data, and clinical or other macroscopic traits, and 2) provides new visualization tools specifically designed to aid in the exploration of association mapping results. Algorithmically, GenAMap is based on a new paradigm for GWAS and PheWAS analysis, termed structured association mapping, which leverages various structures in the omic data.
Provides a tool for building PheWAS websites from association files. Results displayed in this PheWeb include genome-wide associations for EHR-derived ICD-9 billing codes from participants of the Michigan Genomics Initiative. Phenotypes were classified into 1,448 broad PheWAS codes with counts ranging from 20 - 6,083 cases and 5,733 - 18,219 controls. All individuals were genotyped on the Illumina HumanCoreExome Array and imputed using the Haplotype Reference Consortium panel, resulting in around 8 million common variants. Associations were carried out on binary outcomes using a saddlepoint approximation test with adjustment for age, sex, and principal components 1-4. All genomic positions are on GRCh37. This site was built with PheWeb standalone which is available for download.
PHESANT / PHEnome Scan ANalysis Tool
Performs comprehensive phenome scans in UK Biobank, a prospective cohort of over 500 000 men and women in the UK aged between 37-73 years. PHESANT tests the association of a specified trait with all continuous, integer and categorical variables in UK Biobank, or a specified subset. PHESANT uses a novel rule-based algorithm to determine how to appropriately test each trait, then performs the analyses and produces plots and summary tables. These results can be visualised using PHESANT-viz. The aim of this visualisation is to help with interpretation, by allowing the researcher to view each result in the context of the results of related traits.
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