z-logo
open-access-imgOpen Access
isqg: A Binary Framework forin SilicoQuantitative Genetics
Author(s) -
Fernando H. Toledo,
Paulino PérezRodríguez,
José Crossa,
Juan Burgueño
Publication year - 2019
Publication title -
g3 genes genomes genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.468
H-Index - 66
ISSN - 2160-1836
DOI - 10.1534/g3.119.400373
Subject(s) - computer science , inheritance (genetic algorithm) , representation (politics) , binary number , bitwise operation , external data representation , theoretical computer science , genetic programming , range (aeronautics) , binary data , artificial intelligence , mathematics , programming language , genetics , biology , engineering , arithmetic , politics , gene , political science , law , aerospace engineering
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom