isqg: A Binary Framework for in Silico Quantitative Genetics

Autor: Fernando H. Toledo, Paulino Pérez-Rodríguez, José Crossa, Juan Burgueño
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: G3: Genes, Genomes, Genetics, Vol 9, Iss 8, Pp 2425-2428 (2019)
Druh dokumentu: article
ISSN: 2160-1836
DOI: 10.1534/g3.119.400373
Popis: 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.
Databáze: Directory of Open Access Journals