selectMatingIndividuals {ModCon} | R Documentation

## Selecting mating sequences from a pool of sequences

### Description

Selecting sequences from a pool of nucleotide sequences based in chance and their HZEI integral.

### Usage

    selectMatingIndividuals(inputGeneration, whoMatesBestPercent=40, whoMatesSemiRandom=20,
    whoMatesLuckily=5, clust, increaseHZEI=TRUE)

### Arguments

`inputGeneration` | Character vector of nucleotide sequences
`whoMatesBestPercent` | Numeric value e.g. 20 (which would mean that sequences with the top 20 percent highest HZEI integral are selected for mating)
`whoMatesSemiRandom` | Numeric value (is always lower than total number of sequences in input_generation)
`whoMatesLuckily` | Numeric value (is always lower than total number of sequences in input_generation)
`clust` | Name of cluster generated with package parallel
`increaseHZEI` | Logical value of HZEI integral should be increased or decreased during SD degradation. If TRUE, function aims to increase HZEI integral.

### Value

Character vector of nucleotide sequences which are selected from an entered vector of nucleotide sequences `inputGeneration` for creation of filial sequences by recombination. Sequences are selected by different criteria stated by `whoMatesBestPercent`, `whoMatesSemiRandom`, `whoMatesLuckily` and `increaseHZEI`.

### Examples

    ## Setup cluster
    library(parallel)
    nCores <- 1
    clust <- makeCluster(nCores)
    clusterExport(clust, list('getOverlappingVectorsFromVector',
    'hex'), envir=environment())
    selectMatingIndividuals(c('CGCGATACGCGCGATACG','CGCGATACGTGGGATATT',
    'CTAAGCGCTCGCGATACG','CGCGATACGTTAAGCGCT','GACGATAGTCGCGATACG'),
     whoMatesBestPercent=40, whoMatesSemiRandom=1, whoMatesLuckily=1, clust, increaseHZEI=TRUE)

[Package ModCon version 1.0.0 Index]