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About the Genomic Data Sharing (GDS) Policy

Sharing genomic research data is essential for translating research results into knowledge, products, and procedures that improve human health. The GDS policy applies to all NIH-funded research (grants, contracts, intramural research) that generates large-scale human or non-human genomic data and the use of the data for subsequent research. The policy applies to all such research, regardless of the funding level. For examples of research projects involving genomic data that may be subject to the policy, see the section on Examples of Projects below. As the GDS policy applies to a broad range of research, a wide array of data repositories will be used. Genomic data should be shared via a supported NIH repository. See the NIH Genomic Data Sharing Repository list.

The GDS policy is in effect for NIH funded:

  • extramural competing grant applications
  • contract proposals
  • intramural projects generating data

Extramural research initiated prior to January 25, 2015 and intramural research prior to August 31, 2015, will continue to operate under the terms of the policies that were in effect when the research began. This includes:

Examples of Projects That Fall Under GDS Policy

The GDS Policy applies to all NCI-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. NCI may choose to apply the GDS Policy to projects generating smaller scale genomic data depending on the state of the science, the needs of the research community, and programmatic priorities. Investigators should consult with appropriate NCI Program Officers or intramural Scientific Directors as early as possible in the genomic research planning process

Thresholds for Large Scale Research Projects

Regardless of study design, NCI anticipates sharing of large scale genomics research data which includes, but is not limited to the following:

Type of Data Data Examples # of Human Specimens (including human cell lines*) # of Model Organisms, Non-Human Cell Lines, Infectious Organisms*
Includes distinct individuals, species, strains, samples, treatments, time points, tissues, single cells, etc. (e.g., data from 25 patients at 4 time points after treatment would reach a 100 sample threshold; data from 50 tumors-normal comparisons would reach a 100 sample threshold)
SNP array data from > 500k single nucleotide polymorphisms (SNPS) GWAS Data 1,000 500
DNA or RNA sequence data from < 100 genes or regions of interest, or transcripts Targeted Sequencing 1,000 500
DNA sequence data from ≥ 100 genes or regions of interest Targeted Sequencing, Whole Exome Sequencing, Whole Genome Sequencing 100 50
Genome-wide RNA sequencing data Transcriptomic Data 100 50
Genome-wide DNA methylation data Bisulfite Sequencing Data 100 50
Genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) data Transcription Factor ChIP-seq, Histone Modification ChIP-seq 100 50
Metagenome (or microbiome) sequencing data 16S rRNA Sequencing, Shotgun Metagenomics, Whole-Genome Microbial Sequencing 100 50
Metatranscriptome sequencing data Microbial/Microbiome Transcriptomics 100 50

Research that does not meet the above criteria and involves instrument calibration exercises and/or statistical or technical methods development is outside the scope of the GDS policy.

Smaller Scale Research Projects

Investigators should consult with appropriate Program Officers or their Intramural Scientific Director (SD) as early as possible to determine if smaller scale research projects should be submitted.
Submission of data from smaller scale research projects may be expected depending on:

  • the state of the science
  • the programmatic priorities of NCI
  • the utility of the data for the research community

Examples of smaller-scale projects that NCI would likely mandate data sharing for include, but are not limited to:

  • projects examining rare cancers, rare-cancer-related outcomes, or rare cancer subtypes
  • projects focusing on under-studied populations
  • mitochondrial DNA sequencing

Definition of a rare disease:

  • FDA: A disease or condition affecting less than 200,000 persons in the United States (Orphan Drug Act Pub L 97-414, as amended 1984)
  • Rare Disease Act 2002: Rare diseases and disorders are those, which affect small patient populations, typically populations smaller than 200,000 individuals in the United States
  • Genetic and Rare Diseases (GARD) list of rare cancers

Informed Consent

NIH-designated data repositories will not accept data generated from samples or cells lines acquired or created before January 25, 2015 unless informed consent has been provided for future research use and broad data sharing.
In some circumstances, broad sharing may not be consistent with the consent of the research participants whose data are including in the dataset. For more information, the NIH has provided Guidance on Consent for Future Research Use and Broad Sharing of Human Genomic and Phenotypic Data Subject to the GDS Policy. Research that was initiated prior to the effective date of the GDS policy will continue to operate under the terms of the policies that were in effect when the research began; however, NIH strongly encourages investigators to comply with the expectations outlined in the policy.

Exceptions to the GDS Policy

In rare cases, NCI will consider requests for an exception to data sharing expectations on a case-by-case basis. Factors that may preclude data sharing include:

To request an exception, investigators should provide a justification and an alternative data sharing plan in the funding application or proposal. Intramural investigators must also have their request signed by the NIH Deputy Director for Intramural Research. The request will be reviewed by appropriate programmatic staff and NCI leadership. 

NCI considers the following when assessing data sharing exception requests:

  • impact of data sharing compliance on scientific merit
  • unique or high-value resource
  • regulatory considerations
  • ethical considerations
  • NIH data sharing exception precedents
  • having an acceptable alternative data sharing plan (ADSP)
  • impact of ADSP on data re-use and discoverability
  • burden and feasibility

If an exception is granted, the study information will be publicly available in the database of Genotypes and Phenotypes (dbGaP).