Opportunity Information: Apply for RFA HG 21 030
The NIH funding opportunity RFA HG 21 030 supports the creation of Data Analysis and Validation Centers for a new consortium program called Molecular Phenotypes of Null Alleles in Cells (MorPhiC). MorPhiC is built around a long-term, community-facing goal: producing a consistent, gene-by-gene catalog of molecular and cellular phenotypes that result when a human gene is knocked out (a null allele), measured in vitro using multicellular experimental systems. The intent is that this catalog becomes a broadly useful reference for biomedical researchers, enabling systematic comparisons across genes, cell types, and assay modalities, and helping connect gene function to measurable cellular states.
This announcement specifically covers Phase I of the program, which is designed as a practical proving ground before scaling to the entire genome. In Phase I, the consortium will focus on a shared target set of about 1,000 protein-coding genes. The work in this phase is meant to optimize and stress-test the approaches used to generate null alleles and measure downstream phenotypic consequences. Phase I also explicitly emphasizes identifying scale limitations (what breaks when you try to do this at large scale), establishing common data formats so results can be integrated across sites, and developing real-world use cases that demonstrate how the resulting catalog will be used by scientists.
Within that broader structure, the Data Analysis and Validation Centers funded under this FOA are intended to be the computational and analytical backbone that helps ensure the data are interpretable, comparable, and ultimately useful. These centers are expected to develop computational models as well as data analysis, quality assessment, and visualization methods tailored to MorPhiC outputs. In practical terms, that typically means creating pipelines and statistical frameworks to evaluate data quality and reproducibility, detect batch effects and other technical artifacts, quantify phenotypic signals in a consistent way across assays and systems, and provide analytic approaches that translate raw measurements into interpretable phenotypic readouts. Just as importantly, the emphasis on validation implies methods to confirm that observed phenotypes are credible and robust, not just noise or site-specific technical signatures. The visualization component signals an expectation that funded groups will also help design ways to explore and compare phenotypes across genes and experimental contexts, supporting both consortium internal decision-making and eventual public consumption of the data.
This FOA is one of three coordinated announcements that together form the MorPhiC program. Separate companion FOAs cover (1) Data Production Research and Development Centers, which will generate the experimental null alleles and phenotype measurements, and (2) a Data Resource and Administrative Coordination Center, which will receive, annotate, and present consortium data for both consortium members and the broader public, while also serving as the administrative hub for coordination. The Data Analysis and Validation Centers funded here are meant to interact closely with those other components, shaping standards and analyses that make cross-center integration possible and guiding decisions about what constitutes reliable, reusable data.
Mechanistically, this opportunity uses a U01 cooperative agreement, meaning NIH expects substantial programmatic involvement and coordination, rather than a hands-off grant structure. The activity is in the health research category (CFDA 93.172) and explicitly states that clinical trials are not allowed, reinforcing that the work is centered on in vitro systems, data generation/analysis infrastructure, and computational validation rather than human interventional studies. The original closing date listed is November 1, 2021, and the sponsoring agency is the National Institutes of Health.
Eligibility is broad and includes many common applicant types such as universities (public and private), nonprofits (including 501(c)(3) and non-501(c)(3)), for-profit organizations (other than small businesses), small businesses, and multiple levels of government (state, county, city/township, special districts), as well as independent school districts and public housing authorities/Indian housing authorities. The FOA also highlights expanded categories of eligible applicants, including Alaska Native and Native Hawaiian Serving Institutions, AANAPISIs, Hispanic-serving Institutions, HBCUs, Tribally Controlled Colleges and Universities, tribal governments and organizations (including those other than federally recognized in the specified category), faith-based or community-based organizations, U.S. territories or possessions, regional organizations, eligible federal agencies, and non-U.S. entities (foreign organizations). Overall, the opportunity is designed to pull in strong computational and data-science teams capable of building rigorous, scalable analysis and validation approaches that will make the MorPhiC null-allele phenotype catalog dependable and broadly usable.Apply for RFA HG 21 030
- The National Institutes of Health in the health sector is offering a public funding opportunity titled "Molecular Phenotypes of Null Alleles in Cells (MorPhiC) Phase I: Data Analysis and Validation Centers (U01 Clinical trials not allowed)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.172.
- This funding opportunity was created on 2021-08-06.
- Applicants must submit their applications by 2021-11-01. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.
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Frequently Asked Questions (FAQs)
What is NIH RFA HG 21 030 funding?
NIH RFA HG 21 030 funds the creation of Data Analysis and Validation Centers for the Molecular Phenotypes of Null Alleles in Cells (MorPhiC) consortium. These centers are intended to provide the computational and analytical backbone needed to make MorPhiC data interpretable, comparable across sites, and broadly useful to the research community.
What is the MorPhiC program trying to accomplish overall?
MorPhiC has a long-term, community-facing goal of producing a consistent, gene-by-gene catalog of molecular and cellular phenotypes that occur when a human gene is knocked out (a null allele). These phenotypes are measured in vitro using multicellular experimental systems, with the intent that the resulting catalog becomes a reference resource for biomedical researchers.
What is a "null allele" in the context of MorPhiC?
In this program, a null allele refers to a knocked-out human gene, meaning the gene is disrupted such that its function is effectively removed. MorPhiC focuses on measuring the downstream molecular and cellular phenotypes associated with those knockouts.
What phase of the MorPhiC program does this FOA cover?
This announcement covers Phase I of MorPhiC, which is designed as a practical proving ground to optimize and stress-test methods before scaling to a larger portion of the genome.
What is the scope of Phase I?
Phase I focuses on a shared target set of about 1,000 protein-coding genes. The goal is to refine and evaluate approaches for generating null alleles and measuring phenotypic consequences, while identifying scale limitations and establishing common data formats and practical use cases.
What are Data Analysis and Validation Centers expected to do?
Data Analysis and Validation Centers are expected to develop computational models and methods for data analysis, quality assessment, validation, and visualization tailored to MorPhiC outputs. The intention is to ensure results are reliable, reproducible, and integrable across different assays, systems, and sites.
What kinds of computational or analytic capabilities are implied for these centers?
Based on the opportunity description, these centers typically build pipelines and statistical frameworks to evaluate data quality and reproducibility, detect batch effects and other technical artifacts, quantify phenotypic signals consistently across assays and systems, and translate raw measurements into interpretable phenotypic readouts.
What does "validation" mean for this program?
Validation emphasizes methods to confirm that observed phenotypes are credible and robust rather than noise or site-specific technical signatures. The goal is to increase confidence that phenotypes reflect real biological effects of gene knockout.
Why is visualization specifically mentioned?
The visualization expectation signals that funded groups should help design ways to explore and compare phenotypes across genes and experimental contexts. This supports both internal consortium decision-making and eventual public consumption of the cataloged results.
How do these centers fit into the broader MorPhiC consortium?
These centers are one of three coordinated components of MorPhiC. They are expected to interact closely with Data Production Research and Development Centers (which generate experimental knockouts and phenotype measurements) and with the Data Resource and Administrative Coordination Center (which receives, annotates, and presents data and also coordinates consortium administration). The analysis/validation centers help shape standards and analyses to enable cross-center integration.
What are the other companion funding opportunities in MorPhiC?
The MorPhiC program includes separate companion FOAs for (1) Data Production Research and Development Centers and (2) a Data Resource and Administrative Coordination Center. This FOA specifically addresses Data Analysis and Validation Centers.
What is the award mechanism for this opportunity?
This opportunity uses a U01 cooperative agreement mechanism. That implies substantial NIH programmatic involvement and coordination, rather than a more hands-off research project grant structure.
Are clinical trials allowed under this FOA?
No. The FOA explicitly states that clinical trials are not allowed. The work is centered on in vitro systems, data generation and analysis infrastructure, and computational validation rather than human interventional studies.
What is the main research setting for MorPhiC measurements?
The measurements are intended to be made in vitro using multicellular experimental systems, focusing on molecular and cellular phenotypes resulting from gene knockouts.
What is the intended public value of the MorPhiC catalog?
The catalog is intended to become a broadly useful reference for biomedical researchers, enabling systematic comparisons across genes, cell types, and assay modalities and helping connect gene function to measurable cellular states.
Why does Phase I emphasize common data formats?
Common data formats are emphasized so results can be integrated across sites and compared consistently. Integration is central to producing a unified, gene-by-gene catalog rather than isolated datasets.
Why does Phase I emphasize identifying scale limitations?
Phase I is designed to uncover what breaks or becomes limiting when attempting large-scale production of knockouts and phenotypic measurements. Identifying those limitations early supports more reliable scaling later.
What kinds of organizations are eligible to apply?
Eligibility is broad and includes universities (public and private), nonprofits (including 501(c)(3) and non-501(c)(3)), for-profit organizations (other than small businesses), small businesses, and multiple levels of government (state, county, city/township, special districts), as well as independent school districts and public housing authorities/Indian housing authorities.
Are tribal and minority-serving institutions included in eligibility?
Yes. The FOA highlights expanded categories including Alaska Native and Native Hawaiian Serving Institutions, AANAPISIs, Hispanic-serving Institutions, HBCUs, Tribally Controlled Colleges and Universities, tribal governments and organizations (including those other than federally recognized in the specified category), and other listed groups.
Are non-U.S. (foreign) organizations eligible?
Yes. The FOA includes non-U.S. entities (foreign organizations) among eligible applicants.
Which federal agency sponsors this funding opportunity?
The sponsoring agency is the National Institutes of Health (NIH).
What is the CFDA number and category stated for this opportunity?
The activity is in the health research category and lists CFDA 93.172.
What was the original closing date listed for this FOA?
The original closing date listed is November 1, 2021.
What types of teams is this opportunity trying to attract?
The description indicates the opportunity is designed to bring in strong computational and data-science teams capable of building rigorous, scalable analysis and validation approaches to make the null-allele phenotype catalog dependable and broadly usable.
How does this FOA support cross-center comparability?
By focusing on quality assessment, reproducibility evaluation, batch-effect detection, consistent signal quantification, and shared standards and formats, the Data Analysis and Validation Centers help ensure outputs from multiple sites can be compared and integrated.
How will the analysis and validation work influence the usefulness of the final catalog?
The consortium aims for a consistent gene-by-gene reference. Analysis and validation methods help ensure phenotypes are interpretable, robust, and standardized across assays and systems, which directly affects whether outside researchers can trust the catalog for comparisons and downstream hypotheses.
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