Increasing the power of meta-analysis of genome-wide association studies to detect heterogeneous effects

MOTIVATION: Meta-analysis is essential to combine the results of genome-wide association studies (GWASs). Recent large-scale meta-analyses have combined studies of different ethnicities, environments and even studies of different related phenotypes. These differences between studies can manifest as...

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發表在:Bioinformatics
Main Authors: Lee, C H, Eskin, E, Han, B
格式: Artigo
語言:Inglês
出版: Oxford University Press 2017
主題:
Ismb/Eccb 2017: The 25th Annual Conference Intelligent Systems for Molecular Biology Held Jointly with the 16th Annual European Conference on Computational Biology, Prague, Czech Republic, July 21–25, 2017
在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC5870848/
https://ncbi.nlm.nih.gov/pubmed/28881976
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btx242
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