Multi-method genome and epigenome wide studies of inflammatory protein levels in healthy older adults - Linear Regression GWAS Proteins

  • Anna Stevenson (Creator)
  • Marion Patxot (Creator)
  • Sven Erik Ojavee (Creator)
  • Qian Zhang (Creator)
  • David Liewald (Creator)
  • Craig Ritchie (Creator)
  • Kathy Evans (Creator)
  • Naomi Wray (Creator)
  • Allan McRae (Creator)
  • Peter Visscher (Creator)
  • Ian Deary (Creator)
  • Matthew Robinson (Creator)
  • Riccardo Marioni (Creator)
  • Elliot Tucker-Drob (Creator)
  • Robert Hillary (Creator)
  • Daniel Trejo baños (Creator)
  • Athanasios Kousathanas (Creator)
  • Daniel Mccartney (Creator)
  • Sarah Harris (Creator)

Dataset

Abstract

This dataset represents one of five datasets which correspond to the study: "Multi-method genome and epigenome wide studies of inflammatory protein levels in healthy older adults". These datasets represent association studies on the levels of the same set of 70 inflammatory proteins. Each dataset represents one of five distinct methods used to perform genome-wide and epigenome-wide association studies on these protein levels. These methods are: Linear Regression GWAS, Linear Regression EWAS, OSCA EWAS, BayesR+ GWAS and BayesR+ EWAS. These analyses were performed as part of the Lothian Birth Cohort 1936 Study. This data relates to summary statistics for GWAS of 70 Olink inflammation proteins - performed by OLS regression GWAS.

Data Citation

Hillary, Robert; Trejo Banos, Daniel; Kousathanas, Athanasios; McCartney, Daniel; Harris, Sarah; Stevenson, Anna; Patxot, Marion; Ojavee, Sven Erik; Zhang, Qian; Liewald, David; Ritchie, Craig; Evans, Kathryn; Tucker-Drob, Elliot; Wray, Naomi; McRae, Allan; Visscher, Peter; Deary, Ian; Robinson, Matthew; Marioni, Riccardo. (2020). Multi-method genome and epigenome wide studies of inflammatory protein levels in healthy older adults - Linear Regression GWAS Proteins, [dataset]. University of Edinburgh. Centre for Cognitive Ageing and Cognitive Epidemiology. https://doi.org/10.7488/ds/2814
Date made available16 Jul 2020
PublisherEdinburgh DataShare

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