Notice Number: NOT-HG-18-011
Key Dates
Release Date: July 17, 2018
PAR-18-843
Issued by
National Human Genome Research Institute (NHGRI)
Purpose
The purpose of this Notice is to clarify the Objectives (Part 2. Section I) and Resource Sharing Plan (Part 2. Section III) in PAR-18-843 (Investigator Initiated Research in Computational Genomics and Data Science (R21 Clinical Trial Not Allowed).
Part 2. Section I. Funding Opportunity Description
Objectives
Through this FOA, NHGRI seeks to fund innovative research efforts in computational genomics, data science, statistics, and bioinformatics for basic or clinical genomic sciences, and broadly applicable to human health and disease, as well as research leading to improvement of existing software or approaches demonstrated to be in broad use by the genomics community.
Research topics appropriate for this FOA include, but are not limited to, development of novel computational, bioinformatics, statistical, or analytical approaches, tools, or software for:
- Interactive analysis and visualization of large genomic data sets.
- Identification or prioritization of disease-causal genetic variants.
- Causal statistical modeling related to genomic research.
- Analysis of single-cell or sub-cellular genomic data both in situ and in dissociated cells.
- Integrating model organism data and information with human data.
- Integrating and interpreting various genomic data types, including sequence data, functional data, phenotypic data, and clinical data.
- Processing and integrating genome sequence data to enhance representation of population variation.
- Processing sequence data for sequence assembly, variant detection (SNPs and SVs), imputation, and resolution of haplotypes.
- Development of efficient and scalable algorithms for compute-intensive genomic applications.
- Achieving major cost reductions in genomic data processing and analysis.
- Enabling scalable and cost-effective curation of FAIR metadata for genomic and phenotypic data.
- Enhancing secure sharing and use of genomic data in combination with clinical data.
- Processing or analyzing new genomic data types, or major improvement in processing or analyzing existing genomic data types.
- Rigorous benchmarking of tools, methods, or algorithms for genomics.
- Hardening an existing widely-used genomic data processing pipeline to enable its reproducible implementation by the biomedical research community.
This FOA does not support:
- Development, maintenance, or curation of genomic databases and other genomic data resources. Applicants considering developing such resources are directed to the Genomic Community Resources (U24) program: https://grants.nih.gov/grants/guide/pa-files/PAR-17-273.html.
- Research relevant to only one or a few diseases or biological systems. Research utilizing a small number of disease models or biological systems for proof-of-concept studies may be acceptable when the resulting methods, tools, approaches, or software are generalizable.
- Development and application of ontologies or controlled vocabularies, or manual curation efforts.
- Basic data science research that is not developed for genomics.
- Significant experimental work. Applicants may propose limited experimental work to test predictions generated as a result of computational approaches and/or inform modeling efforts, but this should not be a major focus of the application.
- Approaches not clearly pertaining to computational genomics and data science and/or lacking relevance to human health and disease.
Modified to read:
Objectives
Through this FOA, NHGRI seeks to fund innovative research efforts in computational genomics, data science, statistics, and bioinformatics for basic or clinical genomic sciences, and broadly applicable to human health and disease, as well as research leading to improvement of existing software or approaches demonstrated to be in broad use by the genomics community.
Applications for R21 awards should describe projects distinct from those supported through the traditional R01 activity code. The R21 grant mechanism is intended to encourage exploratory/developmental research by providing support for the early and conceptual stages of project development.
Research topics appropriate for this FOA include, but are not limited to, development of novel computational, bioinformatics, statistical, or analytical approaches, tools, or software for:
- Interactive analysis and visualization of large genomic data sets.
- Identification or prioritization of disease-causal genetic variants.
- Causal statistical modeling related to genomic research.
- Analysis of single-cell or sub-cellular genomic data both in situ and in dissociated cells.
- Integrating model organism data with human data to derive biomedical insight.
- Integrating and interpreting various genomic data types, including sequence data, functional data, phenotypic data, and clinical data.
- Processing and integrating genome sequence data to enhance representation of population variation.
- Processing sequence data for sequence assembly, variant detection (SNPs and SVs), imputation, and resolution of haplotypes.
- Development of efficient and scalable algorithms for compute-intensive genomic applications, or otherwise achieving major cost reductions in genomic data processing and analysis.
- Enabling scalable and cost-effective curation of FAIR metadata for genomic and phenotypic data.
- Enhancing secure sharing and use of genomic data in combination with clinical data.
- Processing or analyzing new genomic data types, or major improvement in processing or analyzing existing genomic data types.
- Improved and novel methods for integrating prior biological knowledge into machine learning models.
This FOA does not support:
- Development, maintenance, or curation of genomic databases and other genomic data resources. Applicants considering developing such resources are directed to the Genomic Community Resources (U24) program: https://grants.nih.gov/grants/guide/pa-files/PAR-17-273.html .
- Research not generalizable beyond one or a small number of diseases or biological systems. Research utilizing a small number of disease models or biological systems for proof-of-concept studies may be acceptable when the resulting methods, tools, approaches, or software are generalizable.
- Development and application of ontologies or controlled vocabularies, or manual curation efforts.
- Basic data science research that is not developed for genomics.
- Significant experimental work. Applicants may propose limited experimental work to test predictions generated as a result of computational approaches and/or inform modeling efforts, but this should not be a major focus of the application.
- Approaches not clearly pertaining to computational genomics and data science and/or lacking relevance to human health and disease.
Part 2. Section III
Currently reads:
Resource Sharing Plan:
Individuals are required to comply with the instructions for the Resource Sharing Plans as provided in the SF424 (R&R) Application Guide, with the following modification:
- A major goal of this FOA is the development of computational methods and tools that are enabling for the genomics community. Applicants should therefore include detailed plans for open dissemination of methods, software, and tools to the community such that they are readily usable and extensible, where applicable. These should be made freely available to biomedical researchers and educators. There is no prescribed license for software produced by applications responding to this announcement, but any software license selected by applicants should allow for unrestricted redistribution and modification of software.
- Methods, tools, and software should be well-documented and where applicable made available via version-controlled public repositories.
- Where applicable, applicants should describe solutions for portable implementations.
- Solutions that enhance reproducibility when used by the community and ability of the community to integrate into automated pipelines should be emphasized.
- All applications generating data, regardless of the amount of direct costs requested for any one year, should provide a Data Sharing Plan.
- Applications should adhere to the NIH Genomic Data Sharing Policy, including general NHGRI expectations for implementation of this policy.
Modified to read:
Resource Sharing Plan: Individuals are required to comply with the instructions for the Resource Sharing Plans as provided in the SF424 (R&R) Application Guide, with the following modification:
- A major goal of this FOA is the development of computational methods and tools that are enabling for the genomics community. Applicants should therefore include detailed plans for open dissemination of methods, software, and tools to the community such that they are readily usable and extensible, where applicable. These should be made freely available to biomedical researchers and educators. There is no prescribed license for software produced by applications responding to this announcement, but any software license selected by applicants should allow for unrestricted redistribution and modification of software.
- Methods, tools, and software should be well-documented and where applicable made available via version-controlled public repositories.
- Where applicable, applicants should describe solutions for portable implementations.
- Solutions that enhance reproducibility when used by the community and ability of the community to integrate into automated pipelines should be emphasized.
- All applications generating data, regardless of the amount of direct costs requested for any one year, should provide a Data Sharing Plan.
- Applications should adhere to the NIH Genomic Data Sharing Policy, including general NHGRI expectations for implementation of this policy.
- To facilitate sharing of ideas and methods and accelerate advances in computational genomics and data science, grantees will be required to participate actively and openly in one grantee meeting per year. Applicants should describe their plans for participating in grantee meetings and request funds for 1-3 group members to travel to the meeting each year.
All other aspects of this FOA remain the same.
Inquiries
Please direct all inquiries to:
Daniel Gilchrist, Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 301-496-7531
Email: daniel.gilchrist@nih.gov
and Human Services (HHS)
