Record Details


Field	Value

Title	isqg: a binary framework for in silico quantitative genetics

Names	Toledo, F.H. Perez-Rodriguez, P. Crossa, J. Burgueño, J.
Date Issued	2019 (iso8601)
Abstract	The dna is the fundamental basis of genetic information, just as bits are for computers. Whenever computers are used to represent genetic data, the computational encoding must be efficient to allow the representation of processes driving the inheritance and variability. This is especially important across simulations in view of the increasing complexity and dimensions brought by genomics. This paper introduces a new binary representation of genetic information. Algorithms as bitwise operations that mimic the inheritance of a wide range of polymorphisms are also presented. Different kinds and mixtures of polymorphisms are discussed and exemplified. Proposed algorithms and data structures were implemented in C++ programming language and is available to end users in the R package “isqg” which is available at the R repository (cran). Supplementary data are available online.
Genre	Article
Access Condition	Open Access
Identifier	2160-1836 (Print)

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