qtl.LRS {DOQTL} | R Documentation

## QTL mapping with no kinship.

### Description

These are two functions that perform QTL mapping without a kinship matrix. They use the QR decomposition to speed up the computation. Other than for a quick screen or for assessing significance thresholds, we do not recommend mapping without a kinship matrix. They are included for historical reasons

### Usage

      qtl.LRS(pheno, probs, snps, addcovar = NULL)
      permutations.qtl.LRS(pheno, probs, snps, addcovar, nperm = 1000,
      return.val = c("lod", "p"))

### Arguments

`pheno` | Data.frame containing the phenotype data with samples in rows and phenotypes in columns. Sample IDs in rownames and phenotype names in colnames.
`probs` | Numeric three dimenaional array, containing the founder haplotype contributions or genotype probabilities. The sample IDs, founder letter codes and markers IDs must be in dimnames.
`snps` | data.frame containing 4 columns with marker location information. SNP ID, chr, Mb, cM in columns 1 through 4, respectively.
`addcovar` | data.frame or numeric matrix, containing any additive covariates. Sample IDs must be in rownames.
`nperm` | Numeric value containing the number of permutations to run.
`return.val` | Character string containing either "LRS" or "p", indicating the type of return statistic.

### Details

The function performs Haley-Knott regression at the markers using the founder haplotype contributions in probs.

### Value

List containing two elements. LRS: a data.frame containing the LOD scores. coef: numeric matrix containing model coefficients.

### Author(s)

Daniel Gatti

### See Also

`scanone`

### Examples

      ## Not run:  qtl.LRS(pheno, probs, snps, addcovar = NULL)

[Package DOQTL version 1.19.0 Index]