Using NIH Figshare to collect supplementary material associated with a publication

Using NIH Figshare to collect supplementary material associated with a publication


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A case study of Yosuke Tanigawa

Yosuke Tanigawa and his colleagues at Stanford University have used NIH Figshare to share supplementary data relating to a recent publication  in  PLoS  Genetics (1)   and  grouped  it  into  a  collection (2). Because PLoS uses Figshare to store supplementary material from its  publications  and  this  research  was  funded  by  the  National Human Genome Research, Yosuke was able to create a collection combining  his  PLoS  supplementary  material  with  the  additional datasets he made available in NIH Figshare.

They analyzed large-scale population datasets consisting of more than 500,000 individuals and  identified rare protein-altering variants that significantly reduce the risk of glaucoma. “We used the comprehensive health information in the two population cohorts in our study,” said Yosuke. “While we are not allowed to share those individual-level data, we can make the aggregated summary-level association data publicly available, ensuring it’s useful to other researchers.”

Yosuke also has a keen interest in ensuring that the research he conducts is as FAIR as possible: findable, accessible, interoperable, and reusable (3). “At the very least, I’m trying to make sure my research and accompanying datasets are findable by others,” said Yosuke. “It took very little time and effort to make this collection on Figshare, and if it makes it easier for people to find the data, that’s great.”

For  more  information  on  NIH  Figshare,  visit  or  email

Tanigawa, Yosuke; Rivas, Manuel (2020): Datasets described in ‘Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma’. National Institutes of Health. Collection.






Yosuke Tanigawa is a PhD student in Biomedical Informatics in the Department of Biomedical Data Science at Stanford University specializing in population genomics and analysis of large-scale datasets. To find out more about Yosuke’s research, check out his personal website  and his profile on NIH Figshare.

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