Opportunity Information: Apply for PAR 16 070
Apply for PAR 16 070
- The HHS-NIH11 in the health sector is offering a public funding opportunity titled "NIDCR Small Research Grants for Data Analysis and Statistical Methodology Applied to Genome-wide Data (R03)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.121,.
- This funding opportunity was created on Jan 08, 2016 and posted on Jan 08, 2016.
- Applicants must submit their applications by Jan 07, 2019. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $200,000.00 in funding.
- 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 (see text field entitled Additional Information on Eligibility for clarification).
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Opportunity Summary:
This funding opportunity, titled "NIDCR Small Research Grants for Data Analysis and Statistical Methodology Applied to Genome-wide Data (R03)" (Funding Opportunity Number PAR-16-070), is a National Institutes of Health grant run through the National Institute of Dental and Craniofacial Research (NIDCR) within HHS/NIH. It uses the R03 small grant mechanism, which is typically geared toward focused, limited-scope projects that can be completed with relatively modest budgets and shorter timelines compared with larger research awards.
The main goal of the program is to support high-quality research that either (1) performs rigorous statistical analysis using existing genome-wide datasets or (2) develops and/or refines statistical methods specifically suited to genome-wide data, as long as the work is clearly tied to human dental, oral, or craniofacial conditions or traits. In other words, this is not primarily a data-generation award; it is aimed at extracting new biological or clinical insights from data that already exist, or at building better analytic approaches that make those insights possible in the oral and craniofacial health space.
The types of genome-wide data explicitly called out are broad and include genome-wide SNP genotyping, DNA sequencing data, transcriptomic data, metagenomic data, epigenomic data, and gene expression datasets. The common theme is that these are large-scale, high-dimensional data sources where strong statistical design, careful modeling, and appropriate multiple-testing and validation approaches are essential. Projects might focus on uncovering genetic variants associated with oral disease risk, identifying gene expression patterns linked to craniofacial traits, analyzing oral microbiome metagenomics in relation to dental conditions, or applying epigenomic profiles to understand disease mechanisms. On the methods side, applicants can propose new or improved statistical methodology tailored to genome-wide analyses in these topic areas, such as better models for rare variants, integrative methods across multiple omics layers, approaches that address population structure or relatedness, or techniques that improve reproducibility and inference in very large genomic datasets.
In terms of who can apply, eligibility is wide and includes many kinds of organizations: state, county, and city/township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments and other eligible tribal organizations; public housing authorities/Indian housing authorities; nonprofit organizations (both 501(c)(3) and non-501(c)(3), as long as they are not institutions of higher education); for-profit organizations (other than small businesses); small businesses; and other applicants as allowed under the announcement’s additional eligibility language. The funding activity category is Health, and the CFDA numbers listed are 93.121.
The award has a stated ceiling of $200,000, consistent with the small-grant intent to support compact, well-defined projects rather than large multi-year consortia. The opportunity was posted on January 8, 2016, and the final listed closing date was January 7, 2019. Overall, the program is best suited for teams that already have access to relevant genome-wide datasets (or public datasets they can appropriately use), have strong statistical genetics or biostatistics capability, and can clearly connect their analytic or methodological advances to meaningful questions in dental, oral, or craniofacial research.
FAQs: NIDCR Small Research Grants for Data Analysis and Statistical Methodology Applied to Genome-wide Data (R03) - PAR-16-070
What is this funding opportunity?
This opportunity is titled "NIDCR Small Research Grants for Data Analysis and Statistical Methodology Applied to Genome-wide Data (R03)" with Funding Opportunity Number PAR-16-070. It is a National Institutes of Health (NIH) grant administered by the National Institute of Dental and Craniofacial Research (NIDCR) within HHS/NIH, using the R03 small grant mechanism.
What is the main purpose of this R03 program?
The program supports high-quality research focused on (1) rigorous statistical analysis of existing genome-wide datasets and/or (2) development or refinement of statistical methods suited to genome-wide data, as long as the project is clearly tied to human dental, oral, or craniofacial conditions or traits.
Is this award meant to generate new genome-wide data?
No. The program is described as not primarily a data-generation award. It is aimed at extracting new biological or clinical insights from data that already exist, or creating better analytic approaches that enable those insights in dental, oral, and craniofacial research.
What kinds of projects are a good fit for this opportunity?
Projects that fit well include focused efforts to analyze existing genome-wide datasets for dental, oral, or craniofacial questions, and/or projects that develop statistical methodology tailored to genome-wide data in those topic areas.
What types of genome-wide data are specifically included?
The opportunity explicitly calls out a wide range of genome-wide data types, including genome-wide SNP genotyping, DNA sequencing data, transcriptomic data, metagenomic data, epigenomic data, and gene expression datasets.
What is meant by "genome-wide data" in this program context?
In this context, genome-wide data refers to large-scale, high-dimensional data sources where strong statistical design, careful modeling, and appropriate multiple-testing and validation approaches are essential.
What kinds of research questions could be addressed through data analysis?
Examples described include uncovering genetic variants associated with oral disease risk, identifying gene expression patterns linked to craniofacial traits, analyzing oral microbiome metagenomics in relation to dental conditions, and applying epigenomic profiles to understand disease mechanisms, as long as the work stays tied to human dental, oral, or craniofacial conditions or traits.
What kinds of statistical methodology work could be supported?
The program allows proposals for new or improved statistical methods tailored to genome-wide analyses in dental, oral, and craniofacial topic areas. Examples mentioned include better models for rare variants, integrative methods across multiple omics layers, approaches to address population structure or relatedness, and techniques that improve reproducibility and inference in very large genomic datasets.
Does the program require a connection to a specific health area?
Yes. The work must be clearly tied to human dental, oral, or craniofacial conditions or traits.
Who runs and funds this program?
The program is run through the National Institute of Dental and Craniofacial Research (NIDCR), which is part of the National Institutes of Health (NIH) within HHS/NIH.
What grant mechanism does this opportunity use?
It uses the R03 small grant mechanism, which is typically intended for focused, limited-scope projects that can be completed with relatively modest budgets and shorter timelines compared with larger research awards.
What is the maximum award amount (ceiling)?
The stated ceiling is $200,000, consistent with the small-grant intent to support compact, well-defined projects rather than large multi-year consortia.
What is the funding activity category and CFDA number?
The funding activity category is Health, and the CFDA number listed is 93.121.
Which organizations are eligible to apply?
Eligibility is broad and includes: state governments; county governments; city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments and other eligible tribal organizations; public housing authorities/Indian housing authorities; nonprofit organizations (both 501(c)(3) and non-501(c)(3), as long as they are not institutions of higher education); for-profit organizations (other than small businesses); small businesses; and other applicants as allowed under the announcement's additional eligibility language.
Are small businesses eligible?
Yes. Small businesses are explicitly listed as eligible applicants.
Are for-profit organizations eligible?
Yes. For-profit organizations are eligible, including for-profit organizations other than small businesses, and small businesses are also listed separately as eligible.
Are universities and colleges eligible?
Yes. Both public/state-controlled institutions of higher education and private institutions of higher education are listed as eligible.
Are nonprofits eligible?
Yes. Nonprofit organizations are eligible, including 501(c)(3) and non-501(c)(3) organizations, as long as they are not institutions of higher education.
Are government entities eligible?
Yes. Multiple government entity types are listed as eligible, including state, county, city/township, special district governments, independent school districts, and certain housing authorities.
Are tribal governments or tribal organizations eligible?
Yes. Federally recognized Native American tribal governments and other eligible tribal organizations are listed as eligible applicants.
When was this opportunity posted?
The opportunity was posted on January 8, 2016.
What was the final closing date?
The final listed closing date was January 7, 2019.
What kind of team is this program best suited for?
It is best suited for teams that already have access to relevant genome-wide datasets (or public datasets they can appropriately use), have strong statistical genetics or biostatistics capability, and can clearly connect analytic or methodological advances to meaningful questions in dental, oral, or craniofacial research.
Do applicants need to have their own datasets to apply?
The description emphasizes projects that analyze existing datasets and notes it is best suited for teams that already have access to relevant genome-wide datasets or can appropriately use public datasets.
Does the opportunity specify particular genome-wide analysis challenges it expects applicants to handle?
Yes. The description highlights that these are high-dimensional data sources and emphasizes the need for strong statistical design, careful modeling, and appropriate multiple-testing and validation approaches.
Can projects integrate multiple types of omics data?
Yes. The opportunity explicitly mentions integrative methods across multiple omics layers as an example of relevant statistical methodology development for genome-wide analyses.
Can projects focus on issues like population structure or relatedness?
Yes. Approaches that address population structure or relatedness are specifically mentioned as examples of methods work that could fit.
Is metagenomic analysis (for example, oral microbiome data) within scope?
Yes. Metagenomic data are explicitly included, and analyzing oral microbiome metagenomics in relation to dental conditions is given as an example.
Are epigenomic analyses within scope?
Yes. Epigenomic data are explicitly included, and applying epigenomic profiles to understand disease mechanisms is given as an example direction.
Are transcriptomic and gene expression analyses within scope?
Yes. Transcriptomic data and gene expression datasets are explicitly listed as genome-wide data types included in the program.
Is SNP genotyping or DNA sequencing data within scope?
Yes. Genome-wide SNP genotyping and DNA sequencing data are explicitly listed as included genome-wide data types.
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Applicants also applied for:
Applicants who have applied for this opportunity (PAR 16 070) also looked into and applied for these:
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| Ryan White HIV/AIDS Program Part F Dental Reimbursement Program Apply for HRSA 16 089 Funding Number: HRSA 16 089 Agency: HHS-HRSA Category: Health Funding Amount: Case Dependent |
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