A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog.

The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog.

The IGNITE network: a model for genomic medicine implementation and research.

Background: Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility.

Methods: To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.

Data compatibility in the addiction sciences: an examination of measure commonality.

The need for comprehensive analysis to compare and combine data across multiple studies in order to validate and extend results is widely recognized. This paper aims to assess the extent of data compatibility in the substance abuse and addiction (SAA) sciences through an examination of measure commonality, defined as the use of similar measures, across grants funded by the National Institute on Drug Abuse (NIDA) and the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Data were extracted from applications of funded, active grants involving human-subjects research in four scientific areas (epidemiology, prevention, services, and treatment) and six frequently assessed scientific domains.

PhenX RISING: real world implementation and sharing of PhenX measures.

Background: The purpose of this manuscript is to describe the PhenX RISING network and the site experiences in the implementation of PhenX measures into ongoing population-based genomic studies.

Methods: Eighty PhenX measures were implemented across the seven PhenX RISING groups, thirty-three of which were used at more than two sites, allowing for cross-site collaboration. Each site used between four and 37 individual measures and five of the sites are validating the PhenX measures through comparison with other study measures.

Phenotype-Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources.

Rapidly accumulating data from genome-wide association studies (GWASs) and other large-scale studies are most useful when synthesized with existing databases. To address this opportunity, we developed the Phenotype-Genotype Integrator (PheGenI), a user-friendly web interface that integrates various National Center for Biotechnology Information (NCBI) genomic databases with association data from the National Human Genome Research Institute GWAS Catalog and supports downloads of search results. Here, we describe the rationale for and development of this resource.

The PhenX Toolkit pregnancy and birth collections.

Purpose: Pregnancy and childbirth are normal conditions, but complications and adverse outcomes are common. Both genetic and environmental factors influence the course of pregnancy. Genetic epidemiologic research into pregnancy outcomes could be strengthened by the use of common measures, which would allow data from different studies to be combined or compared.

Using PhenX measures to identify opportunities for cross-study analysis.

The PhenX Toolkit provides researchers with recommended, well-established, low-burden measures suitable for human subject research. The database of Genotypes and Phenotypes (dbGaP) is the data repository for a variety of studies funded by the National Institutes of Health, including genome-wide association studies. The dbGaP requires that investigators provide a data dictionary of study variables as part of the data submission process.

Using the PhenX Toolkit to Add Standard Measures to a Study.

The PhenX (consensus measures for Phenotypes and eXposures) Toolkit (https://www.phenxtoolkit.org/) offers high-quality, well-established measures of phenotypes and exposures for use by the scientific community.

The PhenX Toolkit: get the most from your measures.

The potential for genome-wide association studies to relate phenotypes to specific genetic variation is greatly increased when data can be combined or compared across multiple studies. To facilitate replication and validation across studies, RTI International (Research Triangle Park, North Carolina) and the National Human Genome Research Institute (Bethesda, Maryland) are collaborating on the consensus measures for Phenotypes and eXposures (PhenX) project. The goal of PhenX is to identify 15 high-priority, well-established, and broadly applicable measures for each of 21 research domains.

Potential etiologic and functional implications of genome-wide association loci for human diseases and traits.

We have developed an online catalog of SNP-trait associations from published genome-wide association studies for use in investigating genomic characteristics of trait/disease-associated SNPs (TASs). Reported TASs were common [median risk allele frequency 36%, interquartile range (IQR) 21%-53%] and were associated with modest effect sizes [median odds ratio (OR) 1.33, IQR 1.