Computational Analysis of the Encyclopedia of DNA Elements (ENCODE) Data (U01) | Apply Online

Opportunity Summary:

The Computational Analysis of the Encyclopedia of DNA Elements (ENCODE) Data (U01) funding opportunity (RFA-HG-11-025) is an NIH discretionary grant mechanism offered as a cooperative agreement (U01) through the National Human Genome Research Institute program area (CFDA 93.172, Human Genome Research). It was created to push deeper computational and statistical work on the ENCODE and modENCODE data resources by bringing in investigators who are not already part of the main ENCODE project teams. In practical terms, the opportunity is centered on helping the broader research community extract more biological meaning from ENCODE-scale functional genomics datasets and translate those insights into better interpretation of genetic studies, especially studies aimed at understanding disease risk.

The scientific motivation behind the announcement is that ENCODE (focused on human) and modENCODE (focused on key model organisms) have produced extensive catalogs of functional genomic elements, such as regions involved in gene regulation, transcription factor binding, chromatin accessibility, histone modification patterns, and other biochemical signatures associated with function in the genome. As these catalogs became widely used, the next bottleneck shifted from data generation to data interpretation: how to integrate many layers of genome-wide measurements, how to improve analytic approaches for identifying functional elements, and how to connect functional annotations to genetic variants discovered in mapping studies like GWAS and sequencing-based association efforts. This FOA is essentially an invitation for outside computational groups to innovate on methods, integration strategies, and disease-variant interpretation using ENCODE as a core resource.

The types of projects encouraged under this opportunity fall into three broad categories. First, applicants could develop new computational or statistical methods that improve analysis, inference, visualization, interpretation, or quality assessment of ENCODE datasets. This can include algorithms that better detect regulatory elements, models that connect multiple assay types into coherent functional predictions, approaches for handling cell-type specificity, or techniques that quantify uncertainty and reduce false discoveries in genome-wide annotation. Second, applicants could combine ENCODE data with complementary functional genomics data from other efforts to generate new biological insights. That might mean integrating ENCODE with other epigenomic maps, transcriptomic resources, comparative genomics datasets, or disease-focused functional studies to identify conserved regulatory logic, tissue-specific regulatory programs, or novel relationships between regulatory elements and gene expression. Third, applicants could use ENCODE-derived annotations to improve the analysis of disease mapping studies, with the explicit goal of narrowing down associations to likely causal variants, prioritizing variants for functional follow-up, or improving fine-mapping and interpretation by incorporating functional priors derived from ENCODE.

Because the award is a cooperative agreement (U01), the NIH expects an active partnership role rather than a fully hands-off relationship typical of some standard research project grants. In cooperative agreements, NIH program staff commonly provide substantial programmatic involvement, which can include coordinating activities across awards, ensuring that outputs align with program goals, and encouraging data/software dissemination practices that maximize community benefit. While the short synopsis does not spell out specific deliverable requirements, the nature of ENCODE-related computational funding typically implies expectations around producing shareable methods, analyzable outputs, and results that can be used by other researchers working with ENCODE data.

Eligibility for the program is very broad and explicitly includes applicants beyond traditional academic institutions. Eligible organizations listed include public and private institutions of higher education, nonprofits (both 501(c)(3) and certain non-501(c)(3) entities), for-profit organizations (including small businesses and other for-profits), state and local governments (including counties, cities/townships, special districts), independent school districts, public housing authorities/Indian housing authorities, and a range of tribal entities and tribally controlled colleges. The announcement also allows non-U.S. (foreign) institutions to apply, permits non-domestic components of U.S. organizations, and allows foreign components as defined under NIH policy. The inclusion of a wide variety of institutional types reflects the computational and methodological emphasis of the work, where strong contributions can come from academic labs, research institutes, and private-sector analytics groups alike.

Administratively, the opportunity was posted October 4, 2011, with key dates indicating it was a time-limited solicitation: originally closing December 6, 2011, later extended to December 21, 2011, and archived January 21, 2012. There is no cost sharing or matching requirement. The full announcement was hosted on the NIH grants site under the provided link, and NIH Office of Extramural Research (OER) webmaster contact information is included for access or technical issues related to the posting.

In plain terms, this FOA was designed to fund outside teams to do high-impact computational work using ENCODE/modENCODE outputs: invent better analysis tools, integrate ENCODE with other functional genomic resources, and improve the ability of human genetics studies to move from statistical associations to plausible biological mechanisms and causal variants.

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Previous opportunity: Data Analysis and Coordination Center for the Encyclopedia of DNA Elements (ENCODE) (U41)

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