# Implementing the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)

> **NIH NIH U24** · JOHNS HOPKINS UNIVERSITY · 2021 · $645,000

## Abstract

Project Summary
NIH-sponsored biomedical research is increasingly moving to cloud-based data storage and analysis systems.
The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) powers the
next generation of computational genomics research across the NHGRI using cloud-scale data and compute
resources. The platform provides multiple entry points for data access and analysis, including data search with
Gen3, workflows with Terra and Dockstore, notebook environments including Jupyter and RStudio,
Bioconductor packages for analysis leveraging AnVIL APIs and services, and Galaxy instances for interactive
analysis. By providing a unified environment for data management and compute, AnVIL eliminates the need
for data movement, allows for controlled access to sensitive data, and provides elastic computing resources
that can be acquired by researchers as needed.
The NIH Cloud Platform Interoperability (NCPI) effort aims to address interoperability issues across NIH
cloud systems, including AnVIL, by implementing key technologies and standards. We will work with NCPI
working groups to define use cases and lead outreach as well as implement several major technologies within
the AnVIL. First, we will enhance support for the NIH Researcher Auth Service (RAS) to enable researchers to
establish their identity and access data they are authorized to use across Terra and Galaxy. Second, we will
enhance support for the Global Alliance for Genomics and Health (GA4GH) Data Repository Service (DRS) so
that data consumers can access data objects in a single, standard way. Third, we will enhance support in
AnVIL for the Fast Healthcare Interoperability Resources (FHIR) standard. This will facilitate access to
eMERGE and related projects by users in AnVIL and other NCPI platforms. Next, we will develop new
resources and guides for budgeting for cloud computing. For this, we will identify the most commonly used
tools and workflows run within Galaxy, and model the cost of these tools by varying data sets (e.g.,
sequencing coverage or number of genomes) and computational resources (e.g., number of CPUs, peak RAM).
Statistical analysis of results will be published and serve as a tool to decrease cost as a barrier to cloud research
and cloud interoperabily. Finally, interoperability of workflow generation is hampered by the fact that not all
cloud platforms support the same sets of workflow languages. To address this, we will develop a Kubernetes-
based computational engine to link workflows from multiple workflow languages. This work will initially
focus on usage of Snakemake workflows, followed by extending development to support the workflow
languages WDL, CWL and Galaxy workflows using their respective execution engines. This will simplify the
transition from institutional HPC to the cloud and make it possible for researchers to seamlessly execute
workflows across NCPI platforms.

## Key facts

- **NIH application ID:** 10405959
- **Project number:** 3U24HG010263-04S1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Jeremy Goecks
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $645,000
- **Award type:** 3
- **Project period:** 2018-09-21 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10405959

## Citation

> US National Institutes of Health, RePORTER application 10405959, Implementing the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) (3U24HG010263-04S1). Retrieved via MORVS 2026-10-25 from https://api.morvs.ai/grant/nih/10405959. Licensed CC0.

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