PheWAS statistics

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Citations per year

Number of citations per year for the bioinformatics software tool PheWAS

Tool usage distribution map

This map represents all the scientific publications referring to PheWAS per scientific context
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Associated diseases


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PheWAS specifications


Unique identifier OMICS_00242
Name PheWAS
Alternative name Phenome-wide association study
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 0.12.1
Stability Stable
dplyr, ggplot2, phewas
Maintained Yes


No version available



  • person_outline PheWAS
  • person_outline Leena Choi

Publications for Phenome-wide association study

PheWAS citations


Phenome wide association study identifies marked increased in burden of comorbidities in African Americans with systemic lupus erythematosus

PMCID: 5894248
PMID: 29636090
DOI: 10.1186/s13075-018-1561-8

[…] In the PheWAS comparing Caucasians to African Americans with SLE, adjusting for current age and sex, there were 163 codes that met the FDR of 5% (Additional file : Table S1). Compared to Caucasians, African […]


Evaluating phecodes, clinical classification software, and ICD 9 CM codes for phenome wide association studies in the electronic health record

PLoS One
PMCID: 5501393
PMID: 28686612
DOI: 10.1371/journal.pone.0175508

[…] earch[], including the potential to analyze hundreds of human diseases, drug responses, and many observable clinical traits. EHRs have proven particularly useful for phenome-wide association studies (PheWAS); however, currently, there is no EHR-derived “reference phenome” available for such research.[] Most PheWAS, and indeed many other EHR studies, leverage International Classification of Disease […]


Defining the complex phenotype of severe systemic loxoscelism using a large electronic health record cohort

PLoS One
PMCID: 5396866
PMID: 28422977
DOI: 10.1371/journal.pone.0174941

[…] l characteristics and outcomes of the largest known cohort of individuals with systemic loxoscelism to date, leveraging our large de-identified electronic clinical data warehouse. We then performed a phenome-wide association study (PheWAS) of these individuals matched to a control population to identify key differences in ~1800 phenotypes between individuals who develop systemic loxoscelism and th […]


Systems Genetic Validation of the SNP Metabolite Association in Rice Via Metabolite Pathway Based Phenome Wide Association Scans

Front Plant Sci
PMCID: 4661230
PMID: 26640468
DOI: 10.3389/fpls.2015.01027

[…] s between genotypes and phenotypes (van der Sijde et al., ).In the post-GWAS era, a large number of new emerging data make the interpretation of previous GWAS results a challenge. New methods such as PheWAS (Denny et al., ) and pathway-based analyses have been proposed to alleviate this problem.The emergence of large bodies of electronic medical records (EMRs) may help identify gene-disease associ […]


Phenome wide association study (PheWAS) in EMR linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5 IL13 to Eosinophilic Esophagitis

Front Genet
PMCID: 4235428
PMID: 25477900
DOI: 10.3389/fgene.2014.00401

[…] This first pediatric PheWAS finds 38 associations, 24 previously known phenotype-genotype associations in a pediatric population using EMR-linked eMERGE databases and identified 14 new possible associations at beta > 0.8 […]


Phenome wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index

Front Genet
PMCID: 4134007
PMID: 25177340
DOI: 10.3389/fgene.2014.00250

[…] nd Mi, ; Liu et al., ; Hotta et al., ). More studies with larger populations are required to assess the validity of many of these associations. The results of these associations show the power of the PheWAS method to efficiently detect known and novel pleiotropic associations of genetic variants.BMI is an inexact surrogate for adiposity. Indeed, individuals with a high BMI do not necessarily have […]

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PheWAS institution(s)
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
PheWAS funding source(s)
Supported by the Vanderbilt Faculty Research Scholars Fund, American Heart Association (16FTF30130005), BurroughsWellcome Innovation in Regulatory Science Award (1015006), NIH/NCATS (KL2 TR 000446), NIH/NLM (R01-LM0010685), NIH/NIGMS (R01-GM124109).

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