ArticlePloS one2020
Is useful research data usually shared? An investigation of genome-wide association study summary statistics.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prevalence and predictors of data and code sharing in the medical and health sciences: systematic review with meta-analysis of individual participant data.BMJ (Clinical research ed.) · 2023Pooled it
- Incentivising research data sharing: a scoping review.Wellcome open research · 2021Pooled it
- CCAFE: Estimating case and control allele frequencies from GWAS summary statistics.HGG advances · 2026Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Promoting equity in polygenic risk assessment through global collaboration.Nature genetics · 2024Review
- Promoting Data Sharing: The Moral Obligations of Public Funding Agencies.Science and engineering ethics · 2024Article
- Article
- Clinical utility of polygenic risk scores: a critical 2023 appraisal.Journal of community genetics · 2023Article
- Polygenic Scores in the Direct-to-Consumer Setting: Challenges and Opportunities for a New Era in Consumer Genetic Testing.Journal of personalized medicine · 2023Review
- Sharing GWAS summary statistics results in more citations.Communications biology · 2023Article
- SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration.BMC bioinformatics · 2022Article
- Article
- Bench Research Informed by GWAS Results.Cells · 2021Review
- Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps.Nature medicine · 2021Review
- Workshop proceedings: GWAS summary statistics standards and sharing.Cell genomics · 2021Article
- Review
- Systematizing Effective Practice, Embedding It in Standard Practice.Patterns (New York, N.Y.) · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Primary data collected during a research study is often shared and may be reused for new studies. To assess the extent of data sharing in favourable circumstances and whether data sharing checks can be automated, this article investigates summary statistics from primary human genome-wide association studies (GWAS). This type of data is highly suitable for sharing because it is a standard research output, is straightforward to use in future studies (e.g., for secondary analysis), and may be already stored in a standard format for internal sharing within multi-site research projects. Manual checks of 1799 articles from 2010 and 2017 matching a simple PubMed query for molecular epidemiology GWAS were used to identify 314 primary human GWAS papers. Of these, only 13% reported the location of a complete set of GWAS summary data, increasing from 3% in 2010 to 23% in 2017. Whilst information about whether data was shared was typically located clearly within a data availability statement, the exact nature of the shared data was usually unspecified. Thus, data sharing is the exception even in suitable research fields with relatively strong data sharing norms. Moreover, the lack of clear data descriptions within data sharing statements greatly complicates the task of automatically characterising shared data sets.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.