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simGWAS: a fast method for simulation of large scale case–control GWAS summary statistics
Author(s) -
Mary D Fortune,
Chris Wallace
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty898
Subject(s) - computer science , scale (ratio) , statistics , mathematics , physics , quantum mechanics
Methods for analysis of GWAS summary statistics have encouraged data sharing and democratized the analysis of different diseases. Ideal validation for such methods is application to simulated data, where some 'truth' is known. As GWAS increase in size, so does the computational complexity of such evaluations; standard practice repeatedly simulates and analyses genotype data for all individuals in an example study.

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