isqg

In Silico Quantitative Genetics

Accomplish high performance simulations in quantitative genetics. The molecular genetic components are represented by R6/C++ classes and methods. Mimic the meiosis recombination and de novo genetic variability by means a count-location process (Karlin & Liberman, 1978) <doi:10.1073/pnas.75.12.6332>. The core computational algorithm is implemented using 'Boost' dynamic bitsets (Schaling, 2014) [ISBN:978-1937434366]. A mix between low and high level interfaces provides great flexibility and allows user defined extensions and a wide range of applications.

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Description file content

Package
isqg
Type
Package
Title
In Silico Quantitative Genetics
Version
1.2
Date
2019-01-12
Author
Fernando H. Toledo [aut, cre], International Maize and Wheat Improvement Center [cph]
Maintainer
Fernando H. Toledo
Description
Accomplish high performance simulations in quantitative genetics. The molecular genetic components are represented by R6/C++ classes and methods. Mimic the meiosis recombination and de novo genetic variability by means a count-location process (Karlin & Liberman, 1978) . The core computational algorithm is implemented using 'Boost' dynamic bitsets (Schaling, 2014) [ISBN:978-1937434366]. A mix between low and high level interfaces provides great flexibility and allows user defined extensions and a wide range of applications.
License
GPL-2 | file LICENSE
Encoding
UTF-8
NeedsCompilation
yes
SystemRequirements
C++11
Imports
Rcpp (>= 0.12.15), R6
LinkingTo
Rcpp, BH
Collate
'ISQG.R' 'Mating.R' 'R6Classes.R' 'Functions.R' 'Trait.R' 'RcppExports.R' 'Hooks.R'
LazyData
true
RoxygenNote
6.0.1
Packaged
2019-02-12 15:45:35 UTC; ftoledo
Repository
CRAN
Date/Publication
2019-02-13 09:30:03 UTC

install.packages('isqg')

1.2

a month ago

Fernando H. Toledo

GPL-2 | file LICENSE

Imports

Rcpp (>= 0.12.15), R6

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