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

2019 ◽  
Vol 35 (19) ◽  
pp. 3852-3854 ◽  
Author(s):  
You Tang ◽  
Xiaolei Liu

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.

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1294 ◽  
Author(s):  
Ilya Y. Zhbannikov ◽  
Konstantin G. Arbeev ◽  
Anatoliy I. Yashin

Simulation is important in evaluating novel methods when input data is not easily obtainable or specific assumptions are needed. We present cophesim, a software to add the phenotype to generated genotype data prepared with a genetic simulator. The output of cophesim can be used as a direct input for different genome wide association study tools. cophesim is available from https://bitbucket.org/izhbannikov/cophesim.


2015 ◽  
Vol 32 (6) ◽  
pp. 946-948 ◽  
Author(s):  
Yan Wen ◽  
Wenyu Wang ◽  
Xiong Guo ◽  
Feng Zhang

Abstract Summary: Pleiotropy is common in the genetic architectures of complex diseases. To the best of our knowledge, no analysis tool has been developed for identifying pleiotropic pathways using multiple genome-wide association study (GWAS) summaries by now. Here, we present PAPA, a flexible tool for pleiotropic pathway analysis utilizing GWAS summary results. The performance of PAPA was validated using publicly available GWAS summaries of body mass index and waist-hip ratio of the GIANT datasets. PAPA identified a set of pleiotropic pathways, which have been demonstrated to be involved in the development of obesity. Availability and implementation : PAPA program, document and illustrative example are available at http://sourceforge.net/projects/papav1/files/. Contact : [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.


2009 ◽  
Vol 42 (05) ◽  
Author(s):  
B Konte ◽  
I Giegling ◽  
AM Hartmann ◽  
H Konnerth ◽  
P Muglia ◽  
...  

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1701-P
Author(s):  
LAUREN E. WEDEKIND ◽  
WEN-CHI HSUEH ◽  
SAYUKO KOBES ◽  
MUIDEEN T. OLAIYA ◽  
WILLIAM C. KNOWLER ◽  
...  

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1703-P ◽  
Author(s):  
SHYLAJA SRINIVASAN ◽  
JENNIFER TODD ◽  
LING CHEN ◽  
JASMIN DIVERS ◽  
SAM GIDDING ◽  
...  

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