Nature Communications (Dec 2021)

Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors

  • Wenhan Chen,
  • Yang Wu,
  • Zhili Zheng,
  • Ting Qi,
  • Peter M. Visscher,
  • Zhihong Zhu,
  • Jian Yang

DOI
https://doi.org/10.1038/s41467-021-27438-7
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 10

Abstract

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Analyses of summary statistics from GWAS are subject to biases due to errors in the discovery GWAS or linkage disequilibrium reference data set or heterogeneity between data sets. Here, the authors propose a quality control method to be added to analysis of GWAS summary data that can reduce such biases.