"The UK Biobank recently released genome-wide association data on ~500,000 individuals. The genotype data for these samples have been cleaned, imputed and released to the scientific community. This public release of data represents an extraordinary advance for genetics, pushing the envelope for data sharing and rapid uptake by the research community. These data will be used for novel discovery of disease-associated genes, in the development of new methods, and to serve as an example for how future efforts in genetics and biology ought to proceed.
To further enhance the value of this resource, we have performed a basic association test on ~337,000 unrelated individuals of British ancestry for over 2,000 of the available phenotypes. We’re making these results available for browsing through several portals, including the Global Biobank Engine where they will appear soon. They are also available for download here.
We have decided not to write a scientific article for publication based on these analyses. Rather, we have described the data processing in a detailed blog post linked to the underlying code repositories. The decision to eschew scientific publication for the basic association analysis is rooted in our view that we will continue to work on and analyze these data and, as a result, writing a paper would not reflect the current state of the scientific work we are performing. Our goal here is to make these results available as quickly as possible, for any geneticist, biologist or curious citizen to explore. This is not to suggest that we will not write any papers on these data, but rather only write papers for those activities that involve novel method development or more complex analytic approaches. A univariate genome-wide association analysis is now a relatively well-established activity, and while the scale of this is a bit grander than before, that in and of itself is a relatively perfunctory activity. Simply put, let the data be free.
We do view these results as likely to change as we continue to refine the quality control analyses and as we continue to dig into the results themselves. Nevertheless, we’ve started to use them in a variety of downstream analyses and for other scientific projects and hope that others find them useful too."
'via Blog this'
To further enhance the value of this resource, we have performed a basic association test on ~337,000 unrelated individuals of British ancestry for over 2,000 of the available phenotypes. We’re making these results available for browsing through several portals, including the Global Biobank Engine where they will appear soon. They are also available for download here.
We have decided not to write a scientific article for publication based on these analyses. Rather, we have described the data processing in a detailed blog post linked to the underlying code repositories. The decision to eschew scientific publication for the basic association analysis is rooted in our view that we will continue to work on and analyze these data and, as a result, writing a paper would not reflect the current state of the scientific work we are performing. Our goal here is to make these results available as quickly as possible, for any geneticist, biologist or curious citizen to explore. This is not to suggest that we will not write any papers on these data, but rather only write papers for those activities that involve novel method development or more complex analytic approaches. A univariate genome-wide association analysis is now a relatively well-established activity, and while the scale of this is a bit grander than before, that in and of itself is a relatively perfunctory activity. Simply put, let the data be free.
We do view these results as likely to change as we continue to refine the quality control analyses and as we continue to dig into the results themselves. Nevertheless, we’ve started to use them in a variety of downstream analyses and for other scientific projects and hope that others find them useful too."
'via Blog this'
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