deMeta: Removing sub-studies from meta-analysis of genome wide association studies (GWAS)

Sun, J.; Wang, Y.

doi:10.1101/2020.10.25.354191

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bioRxiv · 10.1101/2020.10.25.354191

deMeta: Removing sub-studies from meta-analysis of genome wide association studies (GWAS)

Sun, J.·Wang, Y.

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Abstract

SummaryPost-GWAS studies using the results from large consortium meta-analysis often need to correctly take care of the overlapping sample issue. The gold standard approach for resolving this issue is to reperform the GWAS or meta-analysis excluding the overlapped participants. However, such approach is time-consuming and, sometimes, restricted by the available data. deMeta provides a user friendly and computationally efficient command-line implementation for removing the effect of a contributing sub-study to a consortium from the meta-analysis results. Only the summary statistics of the meta-analysis the sub-study to be removed are required. In addition, deMeta can generate contrasting Manhattan and quantile-quantile plots for users to visualize the impact of the sub-study on the meta-analysis results. Availability and ImplementationThe python source code, examples and documentations of deMeta are publicly available at https://github.com/Computational-NeuroGenetics/deMeta-beta. Contactjiangming.sun@med.lu.se (J. Sun); yunpeng.wang@psykologi.uio.no (Y. Wang) Supplementary informationNone.

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Sun, J., Wang, Y.. 2020-10-26. deMeta: Removing sub-studies from meta-analysis of genome wide association studies (GWAS). https://doi.org/10.1101/2020.10.25.354191

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