Article Synopsis

  • AnVIL is a cloud-based platform designed to help researchers effectively store, manage, and analyze genomic data within a unified environment.
  • It enhances data sharing and collaboration by allowing researchers to work with various analysis tools (like Terra and Galaxy) without needing to move data around, ensuring better security.
  • The platform supports large-scale genomic studies and continuous improvements in features to facilitate responsible data sharing and accessibility for researchers.

Video Abstracts
Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863334PMC
http://dx.doi.org/10.1016/j.xgen.2021.100085DOI Listing

Publication Analysis

Top Keywords

data sharing
20
data
13
genomics data
12
genomic data
12
nhgri genomic
8
data science
8
analysis
8
science analysis
8
analysis visualization
8
visualization informatics
8

Similar Publications

Introduction: We compared and measured alignment between the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard used by electronic health records (EHRs), the Clinical Data Interchange Standards Consortium (CDISC) standards used by industry, and the Uniform Data Set (UDS) used by the Alzheimer's Disease Research Centers (ADRCs).

Methods: The ADRC UDS, consisting of 5959 data elements across eleven packets, was mapped to FHIR and CDISC standards by two independent mappers, with discrepancies adjudicated by experts.

Results: Forty-five percent of the 5959 UDS data elements mapped to the FHIR standard, indicating possible electronic obtainment from EHRs.

View Article and Find Full Text PDF

Background: Older adults in rural China bear a significant proportion of their healthcare expenses through out-of-pocket payments, resulting in a considerable financial burden on their families.

Objective: This study aimed to explore the key factors influencing adult children's involvement in financing healthcare expenses for their elderly parents in rural China.

Methods: Data were collected by in-depth interviews using a semi-structured interview guide approved by all researchers.

View Article and Find Full Text PDF

Adult congenital heart disease (ACHD) constitutes a heterogeneous and expanding patient cohort with distinctive diagnostic and management challenges. Conventional detection methods are ineffective at reflecting lesion heterogeneity and the variability in risk profiles. Artificial intelligence (AI), including machine learning (ML) and deep learning (DL) models, has revolutionized the potential for improving diagnosis, risk stratification, and personalized care across the ACHD spectrum.

View Article and Find Full Text PDF

Transmission networks of long-term and short-term knowledge in a foraging society.

PNAS Nexus

September 2025

Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig 04103, Germany.

Cultural transmission across generations is key to cumulative cultural evolution. While several mechanisms-such as vertical, horizontal, and oblique transmission-have been studied for decades, how these mechanisms change across the life course, beyond childhood, remains unclear. Furthermore, it is under-explored whether different mechanisms apply to distinct learning processes: long-term learning-where individuals invest time and effort to acquire skills-and short-term learning-where individuals share information of immediate use.

View Article and Find Full Text PDF

Prurigo nodularis (PN) is a chronic skin inflammatory condition characterized by severe, persistent itching and excoriated nodules induced by scratching. PN is strongly related to neural and immune dysfunction and negatively impacts quality of life. Treatments for PN are often off-label, highlighting the need for specifically approved agents and consensus guidelines for patient management.

View Article and Find Full Text PDF