cash-addSNPs: BC and FS method: Add MI, PI and SI SNPs to existing linkage...

In tpbilton/GUSMap: Genotyping Uncertainty with Sequencing Data and Linkage Mapping (GUSMap)

BC and FS method: Add MI, PI and SI SNPs to existing linkage groups

Description

Method for adding maternal-informative (MI), paternal-informative (PI) and semi-informative (SI) SNPs to the paternal and maternal (pseudo-testcross) linkage groups.

Usage

BCobj$addSNPs(LODthres = 10, nComp = 30)
FSobj$addSNPs(LODthres = 10, nComp = 30)

Arguments

LODthres	A positive numeric value specifying the LOD threshold used to add SNPs to the linkage groups.
nComp	A positive integer value specifying how many SNPs in the linkage group to compute the average LOD score with the unmapped SNP.

Details

Each MI, PI or SI SNP is mapped to the maternal and paternal linkage groups using the following algorithm:

1. For each pseudo-testcross linkage group, compute the average LOD score between the unmapped SNP and a specified number (nComp) of SNPs in the pseudo-testcross linkage group that have the highest LOD score with the unmapped SNP.

2. Map the unmapped SNP to the pseudo-testcross linkage group with the highest average LOD score if:

   • The largest average LOD score is greater than the LOD threshold (LODthres).

   • All the other average LOD scores associated with the other linkage groups are less than the LOD threshold.

Author(s)

Timothy P. Bilton

See Also

BC, FS

Examples

## Simulate some sequencing data
set.seed(6745)
config <- list(list(sample(c(1,2,4), size=30, replace=TRUE)))
F1data <- simFS(0.01, config=config, meanDepth=10, nInd = 50)
## Compute 2-point recombination fractions
F1data$rf_2pt()
## create paternal and maternal linkage groups
F1data$createLG()

## Add more SNPs to the linkage groups
F1data$addSNPs()

tpbilton/GUSMap documentation built on Feb. 22, 2025, 12:27 p.m.