G2P: A Genome-Wide-Association-Study simulation tool for genotype simulation, phenotype simulation and power evaluation

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Abstract

Motivation: Plenty of Genome-Wide-Association-Study (GWAS) methods have been developed for mapping genetic markers that associated with human diseases and agricultural economic traits. Computer simulation is a nice tool to test the performances of various GWAS methods under certain scenarios. Existing tools are either inefficient in terms of computation and memory efficiency or inconvenient to use to simulate big, realistic genotype data and phenotype data to evaluate available GWAS methods. Results: Here, we present a GWAS simulation tool named G2P that can be used to simulate genotype data, phenotype data and perform power evaluation of GWAS methods. G2P is a user-friendly tool with all functions is provided in both graphical user interface and pipeline manners and it is available for Windows, Mac and Linux environments. Furthermore, G2P achieves maximum efficiency in terms of both memory usage and simulation speed; with G2P, the simulation of genotype data that includes 1 000 000 samples and 2 000 000 markers can be accomplished in 5 h. Availability and implementation: The G2P software, user manual, and example datasets are freely available at GitHub: https://github.com/XiaoleiLiuBio/G2P. Supplementary information: Supplementary data are available at Bioinformatics online.

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Tang, Y., & Liu, X. (2019). G2P: A Genome-Wide-Association-Study simulation tool for genotype simulation, phenotype simulation and power evaluation. Bioinformatics, 35(19), 3852–3854. https://doi.org/10.1093/bioinformatics/btz126

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