rf_2pops: Multipoint recombination fraction based on two mapping...
In rramadeu/onemap2pop: onemap extension for multipopulation

Description Usage Arguments Value Note Author(s) References Examples

View source: R/rf_2pops.R

The function 'rf_2pops' estimates the recombination fraction based on two mapping populations. It estimates the recombination fractions based on a multipoint approach implemented using the methodology of Hidden Markov Models (HMM) with the Expectation Maximization (EM) algorithm as explained in the supplementary material of Quezada et al. (2017).

1 2	rf_2pops(markers_names, data_P1, data_P2, rftwopoints_P1, rftwopoints_P2, LOD = 3, max.rf = 0.5, log10.mintol = -6, max_it = 50)

`data_P1`	an onemap object class with the information of the first population.
`data_P2`	an onemap object class with the information of the second population.
`rftwopoints_P1`	an rf_2pts object with the information of rf from the first population.
`rftwopoints_P2`	an rf_2pts object with the information of rf from the second population.
`LOD`	minimum LOD Score to declare linkage (defaults to `3`).
`max.rf`	maximum recombination fraction to declare linkage (defaults to `0.50`).
`log10.mintol`	log base 10 of the minimum tolerance to converge the EM (defaults to `-6`)
`max_it`	maximum number of iteration to converge the EM (defaults to `50`)
`marker_names`	an vector of strings with the marker order.

A list with two objects of class rf_2pts, one for each population and the log-likelihood of the composite map

The thresholds used for LOD and max.rf will be used in subsequent analyses, but can be overriden.

Rodrigo R Amadeu rramadeu@gmail.com and Marianella Quezada marianellaquezada@gmail.com

Quezada et al. 2018

notrun{
data(onemap2pop)
#Extracting the marker names:
order_LG1POP1 <- colnames(POP1.geno$geno)[LG1_POP1_final$seq.num]
#Computing the rf and likelihood considering information of POP1 and POP2
LG1_POP1order <- rf_2pops(markers_names=order_LG1POP1,
                          data_P1=POP1_geno,
                          data_P2=POP2_geno,
                          rftwopoints_P1 = twopts_POP1,
                          rftwopoints_P2 = twopts_POP2,
                          LOD=3,
                          max.rf=0.5,
                          log10.mintol = -6,
                          max_it = 60)
}