TY  - JA
AU  - Toledo,F.H.
AU  - Perez-Rodriguez,P.
AU  - Crossa,J.
AU  - Burgueño,J.
TI  - isqg : : a binary framework for in silico quantitative genetics
SN  - 2160-1836
PY  - 2019///
CY  - Bethesda, MD (USA)
PB  - Genetics Society of America
KW  - AGROVOC
KW  - Bioinformatics
KW  - Recombination
KW  - Simulation
KW  - Genetics
N1  - Peer review; Open Access
N2  - 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
UR  - https://hdl.handle.net/10883/20224
DO  - https://doi.org/10.1534/g3.119.400373
T2  - G3: Genes, Genomes, Genetics
ER  -