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

Journal ArticleOPEN ACCESS

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

Chen W
Wu Y
Zheng Z
et al.

Nature Communications (2021) 12(1)

DOI: 10.1038/s41467-021-27438-7

26Citations

93Readers

Abstract

28% to <2% in the presence of heterogeneity between GWAS and LD reference). We further show that DENTIST can improve other summary-data-based analyses such as fine-mapping analysis.

Cite

CITATION STYLE

APA

Chen, W., Wu, Y., Zheng, Z., Qi, T., Visscher, P. M., Zhu, Z., & Yang, J. (2021). Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors. Nature Communications, 12(1). https://doi.org/10.1038/s41467-021-27438-7

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

Abstract

Cite

Register to see more suggestions