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Genetic Data Simulators and their Applications: An Overview
Author(s) -
Peng Bo,
Chen HuannSheng,
Mechanic Leah E.,
Racine Ben,
Clarke John,
Gillanders Elizabeth,
Feuer Eric J.
Publication year - 2015
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.21876
Subject(s) - computer science , software , perspective (graphical) , data science , reliability (semiconductor) , focus (optics) , software engineering , systems engineering , artificial intelligence , engineering , power (physics) , physics , quantum mechanics , optics , programming language
Computer simulations have played an indispensable role in the development and applications of statistical models and methods for genetic studies across multiple disciplines. The need to simulate complex evolutionary scenarios and pseudo‐datasets for various studies has fueled the development of dozens of computer programs with varying reliability, performance, and application areas. To help researchers compare and choose the most appropriate simulators for their studies, we have created the genetic simulation resources (GSR) website, which allows authors of simulation software to register their applications and describe them with more than 160 defined attributes. This article summarizes the properties of 93 simulators currently registered at GSR and provides an overview of the development and applications of genetic simulators. Unlike other review articles that address technical issues or compare simulators for particular application areas, we focus on software development, maintenance, and features of simulators, often from a historical perspective. Publications that cite these simulators are used to summarize both the applications of genetic simulations and the utilization of simulators.