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Data from the Asia Pacific Cohort Studies Collaboration (APCSC), a large scale individual data pooling project based in Asia and Australasia Australia and New Zealandd), affords us the opportunity to make such a comparison.
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Until that cultural shift happens at a larger scale, individuals like Pfortmüller are left bridging the gaps on their own.
We implement this model in a large-scale individual-based simulation, and in doing so, we find a remarkable correspondence between model behavior and observed influenza dynamics.
We implemented this geometrical model in a large-scale individual-based simulation intended to directly model the antigenic map and genealogical tree of the global influenza population.
We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data.
As the number of large-scale individual-participant meta-analyses and the amount of data sharing increase within the research community, epidemiology as a science can become more transparent and self-critical.
To characterize the joint epidemiological, genealogical, antigenic, and spatial patterns of influenza, we implemented a large-scale individual-based model (full simulation source code available at http://www.trevorbedford.com/antigen/).
Establishing the optimal way of combining external summary statistics with data statistics is of practical importance as it can lead to improved genomic predictors without the need to access large-scale individual-level data.
A practical implication of this is that we can improve the accuracy of genetic predictors without the need to access large-scale individual-level data sets, and we can potentially combine multiple predictors based on different summary statistics, e.g. combine risk scores based on multiple GWAS studies if a GWAMA is not available.
Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results.
We detected large scale declines in individual species.
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