R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment.
paper
Cited
Public
Unavailable
- Authors
- Carroll, Robert J; Bastarache, Lisa; Denny, Joshua C
- Year
- 2014
- Journal
- Bioinformatics (Oxford, England)
- PMID
- 24733291
- DOI
- 10.1093/bioinformatics/btu197
- PMCID
- PMC4133579
UNLABELLED: Phenome-wide association studies (PheWAS) have been used to replicate known genetic associations and discover new phenotype associations for genetic variants. This PheWAS implementation allows users to translate ICD-9 codes to PheWAS case and control groups, perform analyses using these and/or other phenotypes with covariate adjustments and plot the results. We demonstrate the methods by replicating a PheWAS on rs3135388 (near HLA-DRB, associated with multiple sclerosis) and performing a novel PheWAS using an individual's maximum white blood cell count (WBC) as a continuous measure. Our results for rs3135388 replicate known associations with more significant results than the original study on the same dataset. Our PheWAS of WBC found expected results, including associations with infections, myeloproliferative diseases and associated conditions, such as anemia. These results demonstrate the performance of the improved classification scheme and the flexibility of PheWAS encapsulated in this package. AVAILABILITY AND IMPLEMENTATION: This R package is freely available under the Gnu Public License (GPL-3) from http://phewascatalog.org. It is implemented in native R and is platform independent.
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| Pleiotropic genetic architecture and novel loci for C-reactive protein levels. | Koskeridis F et al. | β | 2022 | β |
| Polygenic Liability to Depression Is Associated With Multiple Medical Conditions in the Electronic Health Record: Phenome-wide Association Study of 46,782 Individuals. | Fang Y et al. | β | 2022 | β |
| Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort. | PrivΓ© F et al. | β | 2022 | β |
| Psychiatric manifestations of rare variation in medically actionable genes: a PheWAS approach. | Feng YA et al. | β | 2022 | β |
| pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis. | Kerley CI et al. | β | 2022 | β |
| Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics. | Robinson JR et al. | β | 2022 | β |
| Stroke genetics informs drug discovery and risk prediction across ancestries. | Mishra A et al. | β | 2022 | β |
| Systems Approach to Integrating Preclinical Apolipoprotein E-Knockout Investigations Reveals Novel Etiologic Pathways and Master Atherosclerosis Network in Humans. | Shuey MM et al. | β | 2022 | β |
| The <i>All of Us</i> Research Program: Data quality, utility, and diversity. | Ramirez AH et al. | β | 2022 | β |
| Using phenome-wide association studies and the SF-12 quality of life metric to identify profound consequences of adverse childhood experiences on adult mental and physical health in a Northern Nevadan population. | Schlauch KA et al. | β | 2022 | β |
| Alcohol and cigarette smoking consumption as genetic proxies for alcohol misuse and nicotine dependence. | Sanchez-Roige S et al. | β | 2021 | β |
| An Explainable Multimodal Neural Network Architecture for Predicting Epilepsy Comorbidities Based on Administrative Claims Data. | Linden T et al. | β | 2021 | β |
| Associations of Genetically Predicted Lp(a) (Lipoprotein [a]) Levels With Cardiovascular Traits in Individuals of European and African Ancestry. | Satterfield BA et al. | β | 2021 | β |
| Childhood Obesity and Risk of Stroke: A Mendelian Randomisation Analysis. | Zou XL et al. | β | 2021 | β |
| Cognitive disorders associated with hospitalization of COVID-19: Results from an observational cohort study. | Zhou J et al. | β | 2021 | β |
| Comparing Genetic and Socioenvironmental Contributions to Ethnic Differences in C-Reactive Protein. | Nagar SD et al. | β | 2021 | β |
| Copy Number Variant Analysis and Genome-wide Association Study Identify Loci with Large Effect for Vesicoureteral Reflux. | Verbitsky M et al. | β | 2021 | β |
| COVID-19 susceptibility variants associate with blood clots, thrombophlebitis and circulatory diseases. | Papadopoulou A et al. | β | 2021 | β |
| Deciphering the genetic and epidemiological landscape of mitochondrial DNA abundance. | HΓ€gg S et al. | β | 2021 | β |
| Disrupting upstream translation in mRNAs is associated with human disease. | Lee DSM et al. | β | 2021 | β |
| Evaluation of the MC4R gene across eMERGE network identifies many unreported obesity-associated variants. | Namjou B et al. | β | 2021 | β |
| Exome-wide evaluation of rare coding variants using electronic health records identifies new gene-phenotype associations. | Park J et al. | β | 2021 | β |
| Fate or coincidence: do COPD and major depression share genetic risk factors? | Martucci VL et al. | β | 2021 | β |
| Genetically Determined Chronic Low-Grade Inflammation and Hundreds of Health Outcomes in the UK Biobank and the FinnGen Population: A Phenome-Wide Mendelian Randomization Study. | Si S et al. | β | 2021 | β |
| Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning. | Liu Y et al. | β | 2021 | β |
| Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease. | Dennis J et al. | β | 2021 | β |
| Genome-wide association study of problematic opioid prescription use in 132,113 23andMe research participants of European ancestry. | Sanchez-Roige S et al. | β | 2021 | β |
| Genome-Wide Identification of Rare and Common Variants Driving Triglyceride Levels in a Nevada Population. | Read RW et al. | β | 2021 | β |
| Genomic and pleiotropic analyses of resting QT interval identifies novel loci and overlap with atrial electrical disorders. | van Duijvenboden S et al. | β | 2021 | β |
| HIF-1Ξ± Pulmonary Phenotype Wide Association Study Unveils a Link to Inflammatory Airway Conditions. | Kelchtermans J et al. | β | 2021 | β |
| Incident disease associations with mosaic chromosomal alterations on autosomes, X and Y chromosomes: insights from a phenome-wide association study in the UK Biobank. | Lin SH et al. | β | 2021 | β |
| Integration of genetic, transcriptomic, and clinical data provides insight into 16p11.2 and 22q11.2 CNV genes. | Vysotskiy M et al. | β | 2021 | β |
| Leveraging electronic health records data to predict multiple sclerosis disease activity. | Ahuja Y et al. | β | 2021 | β |
| Mammographic features are associated with cardiometabolic disease risk and mortality. | Grassmann F et al. | β | 2021 | β |
| Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies. | Shang N et al. | β | 2021 | β |
| Methodology in phenome-wide association studies: a systematic review. | Wang L et al. | β | 2021 | β |
| Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies. | Zhao L et al. | β | 2021 | β |
| Novel EDGE encoding method enhances ability to identify genetic interactions. | Hall MA et al. | β | 2021 | β |
| Phenotype risk scores (PheRS) for pancreatic cancer using time-stamped electronic health record data: Discovery and validation in two large biobanks. | Salvatore M et al. | β | 2021 | β |
| Pleiotropy of systemic lupus erythematosus risk alleles and cardiometabolic disorders: A phenome-wide association study and inverse-variance weighted meta-analysis. | Kawai VK et al. | β | 2021 | β |
| The genetic architecture of plasma kynurenine includes cardiometabolic disease mechanisms associated with the SH2B3 gene. | Bagheri M et al. | β | 2021 | β |
| Using Phecodes for Research with the Electronic Health Record: From PheWAS to PheRS. | Bastarache L | β | 2021 | β |
| A Comprehensive Genome-Wide and Phenome-Wide Examination of BMI and Obesity in a Northern Nevadan Cohort. | Schlauch KA et al. | β | 2020 | β |
| A genome-first approach to aggregating rare genetic variants in LMNA for association with electronic health record phenotypes. | Park J et al. | β | 2020 | β |
| A large-scale genome-wide association study meta-analysis of cannabis use disorder. | Johnson EC et al. | β | 2020 | β |
| An analytic framework for exploring sampling and observation process biases in genome and phenome-wide association studies using electronic health records. | Beesley LJ et al. | β | 2020 | β |
| Apolipoprotein E (APOE) genotype-associated disease risks: a phenome-wide, registry-based, case-control study utilising the UK Biobank. | Lumsden AL et al. | β | 2020 | β |
| A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies. | Joo YY et al. | β | 2020 | β |
| Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization. | Robinson JR et al. | β | 2020 | β |
| Cancer PRSweb: An Online Repository with Polygenic Risk Scores for Major Cancer Traits and Their Evaluation in Two Independent Biobanks. | Fritsche LG et al. | β | 2020 | β |
| Electronic health record analysis identifies kidney disease as the leading risk factor for hospitalization in confirmed COVID-19 patients. | Oetjens MT et al. | β | 2020 | β |
| Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis. | Zhong X et al. | β | 2020 | β |
| Exploring and visualizing large-scale genetic associations by using PheWeb. | Gagliano Taliun SA et al. | β | 2020 | β |
| Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program. | Klarin D et al. | β | 2020 | β |
| Genetics of height and risk of atrial fibrillation: A Mendelian randomization study. | Levin MG et al. | β | 2020 | β |
| Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. | Zhou H et al. | β | 2020 | β |
| Novel and known morbidities of leukodystrophies identified using a phenome-wide association study. | Bonkowsky JL et al. | β | 2020 | β |
| PCSK9 loss of function is protective against extra-coronary atherosclerotic cardiovascular disease in a large multi-ethnic cohort. | Small AM et al. | β | 2020 | β |
| PheGWAS: a new dimension to visualize GWAS across multiple phenotypes. | George G et al. | β | 2020 | β |
| Phenome-wide association analysis suggests the APOL1 linked disease spectrum primarily drives kidney-specific pathways. | Bajaj A et al. | β | 2020 | β |
| Phenome-wide examination of comorbidity burden and multiple sclerosis disease severity. | Zhang T et al. | β | 2020 | β |
| Pleiotropy in the Genetic Predisposition to Rheumatoid Arthritis: A Phenome-Wide Association Study and Inverse Variance-Weighted Meta-Analysis. | Kawai VK et al. | β | 2020 | β |
| Repurposing of a Thromboxane Receptor Inhibitor Based on a Novel Role in Metastasis Identified by Phenome-Wide Association Study. | Werfel TA et al. | β | 2020 | β |
| The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities. | Beesley LJ et al. | β | 2020 | β |
| The polygenic architecture of left ventricular mass mirrors the clinical epidemiology. | Mosley JD et al. | β | 2020 | β |
| Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations. | Chen MH et al. | β | 2020 | β |
| A Genetic Approach to the Association Between PCSK9 and Sepsis. | Feng Q et al. | β | 2019 | β |
| A phenome-wide association study to discover pleiotropic effects of <i>PCSK9</i>, <i>APOB</i>, and <i>LDLR</i>. | Safarova MS et al. | β | 2019 | β |
| Association Between Low-Density Lipoprotein Cholesterol Levels and Risk for Sepsis Among Patients Admitted to the Hospital With Infection. | Feng Q et al. | β | 2019 | β |
| Association of <i>APOL1</i> Risk Alleles With Cardiovascular Disease in Blacks in the Million Veteran Program. | Bick AG et al. | β | 2019 | β |
| Association of Thyroid Function Genetic Predictors With Atrial Fibrillation: A Phenome-Wide Association Study and Inverse-Variance Weighted Average Meta-analysis. | Salem JE et al. | β | 2019 | β |
| Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb. | Fritsche LG et al. | β | 2019 | β |
| Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. | Kranzler HR et al. | β | 2019 | β |
| Genome-wide association study of peripheral artery disease in the Million Veteran Program. | Klarin D et al. | β | 2019 | β |
| Genomics-First Evaluation of Heart Disease Associated With Titin-Truncating Variants. | Haggerty CM et al. | β | 2019 | β |
| GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network. | Namjou B et al. | β | 2019 | β |
| GWAS and PheWAS of red blood cell components in a Northern Nevadan cohort. | Read RW et al. | β | 2019 | β |
| Health effects associated with serum calcium concentrations: evidence from MR-PheWAS analysis in UK Biobank. | Zhou A et al. | β | 2019 | β |
| Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation. | Wu P et al. | β | 2019 | β |
| Operative vs Nonoperative Treatment for Atraumatic Rotator Cuff Tears: A Trial Protocol for the Arthroscopic Rotator Cuff Pragmatic Randomized Clinical Trial. | Jain NB et al. | β | 2019 | β |
| Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems. | Zheutlin AB et al. | β | 2019 | β |
| Phenome-wide association study identifies dsDNA as a driver of major organ involvement in systemic lupus erythematosus. | Barnado A et al. | β | 2019 | β |
| Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness. | Abdellaoui A et al. | β | 2019 | β |
| Phenome-wide Mendelian-randomization study of genetically determined vitamin D on multiple health outcomes using the UK Biobank study. | Meng X et al. | β | 2019 | β |
| Trans-ethnic association study of blood pressure determinants in over 750,000 individuals. | Giri A et al. | β | 2019 | β |
| Unbiased Phenome-Wide Association Studies of Red Cell Distribution Width Identifies Key Associations with Pulmonary Hypertension. | Thayer TE et al. | β | 2019 | β |
| An Atlas of Genetic Variation Linking Pathogen-Induced Cellular Traits to Human Disease. | Wang L et al. | β | 2018 | β |
| Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative. | Fritsche LG et al. | β | 2018 | β |
| Evaluating statistical approaches to leverage large clinical datasets for uncovering therapeutic and adverse medication effects. | Choi L et al. | β | 2018 | β |
| LPA Variants Are Associated With Residual Cardiovascular Risk in Patients Receiving Statins. | Wei WQ et al. | β | 2018 | β |
| MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank. | Li X et al. | β | 2018 | β |
| Phenome-Wide Association Studies Uncover a Novel Association of Increased Atrial Fibrillation in Male Patients With Systemic Lupus Erythematosus. | Barnado A et al. | β | 2018 | β |
| Phenome-wide association study identifies marked increased in burden of comorbidities in African Americans with systemic lupus erythematosus. | Barnado A et al. | β | 2018 | β |
| PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies. | Sinnott JA et al. | β | 2018 | β |
| Rare Variants in the Gene ALPL That Cause Hypophosphatasia Are Strongly Associated With Ovarian and Uterine Disorders. | Dahir KM et al. | β | 2018 | β |
| Recent Genetics and Epigenetics Approaches to PTSD. | Daskalakis NP et al. | β | 2018 | β |
| Relationship between very low low-density lipoprotein cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: A US-based cross-sectional observational study using electronic health records. | Feng Q et al. | β | 2018 | β |
| A Fast and Accurate Algorithm to Test for Binary Phenotypes and Its Application to PheWAS. | Dey R et al. | β | 2017 | β |
| Current Scope and Challenges in Phenome-Wide Association Studies. | Verma A et al. | β | 2017 | β |
| Defining the complex phenotype of severe systemic loxoscelism using a large electronic health record cohort. | Robinson JR et al. | β | 2017 | β |
| Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record. | Wei WQ et al. | β | 2017 | β |
| Hospitalizations for mitochondrial disease across the lifespan in the U.S. | McCormack SE et al. | β | 2017 | β |
| Phenome-Wide Association Study of Rheumatoid Arthritis Subgroups Identifies Association Between Seronegative Disease and Fibromyalgia. | Doss J et al. | β | 2017 | β |
| Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants. | Karnes JH et al. | β | 2017 | β |
| Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods. | Richesson RL et al. | β | 2016 | β |
| Data integration of structured and unstructured sources for assigning clinical codes to patient stays. | Scheurwegs E et al. | β | 2016 | β |
| Heterozygosity Ratio, a Robust Global Genomic Measure of Autozygosity and Its Association with Height and Disease Risk. | Samuels DC et al. | β | 2016 | β |
| Phenome-Wide Association Studies as a Tool to Advance Precision Medicine. | Denny JC et al. | β | 2016 | β |
| Phenome-wide association study maps new diseases to the human major histocompatibility complex region. | Liu J et al. | β | 2016 | β |
| The phenotypic legacy of admixture between modern humans and Neandertals. | Simonti CN et al. | β | 2016 | β |
| Transcription factor ETV1 is essential for rapid conduction in the heart. | Shekhar A et al. | β | 2016 | β |
| Unravelling the human genome-phenome relationship using phenome-wide association studies. | Bush WS et al. | β | 2016 | β |
| Application of clinical text data for phenome-wide association studies (PheWASs). | Hebbring SJ et al. | β | 2015 | β |
| Contrasting Association Results between Existing PheWAS Phenotype Definition Methods and Five Validated Electronic Phenotypes. | Leader JB et al. | β | 2015 | β |
| Desiderata for computable representations of electronic health records-driven phenotype algorithms. | Mo H et al. | β | 2015 | β |
| Proceedings of the 14th Annual UT-KBRIN Bioinformatics Summit 2015. | β | β | 2015 | β |
| Seeing the forest through the trees: uncovering phenomic complexity through interactive network visualization. | Warner JL et al. | β | 2015 | β |
| Systems Genetic Validation of the SNP-Metabolite Association in Rice Via Metabolite-Pathway-Based Phenome-Wide Association Scans. | Lu Y et al. | β | 2015 | β |
| Improved drug therapy: triangulating phenomics with genomics and metabolomics. | Monte AA et al. | β | 2014 | β |
| Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index. | Cronin RM et al. | β | 2014 | β |
| Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to Eosinophilic Esophagitis. | Namjou B et al. | β | 2014 | β |