# Genome Scan for QTL Likelihood ratio tests or F tests at scanning loci over the genome. ```r scanOne(y, x, gdat, prdat = NULL, vc = NULL, intc = NULL, numGeno = FALSE, test = c("None","F","LRT"), minorGenoFreq = 0, rmv = TRUE) ``` ## Arguments - `y`: A numeric vector or a numeric matrix of one column, representing a phenotype. - `x`: A data frame or matrix, representing covariates if not missing. - `gdat`: Genotype data. It should be a matrix or a data frame, with each row being a sample and each column a locus. The column names should be marker names. It is ignored if an object `prdat` from `genoProb` is used as an argument. If `gdat` is not numeric, there can be more than three genotypes and all scanning loci should have the same number of genotypes. - `prdat`: An object from `genoProb`, or in the same form. It should have a class "addEff" if allelic effects are assumed to be additive (see example below). - `vc`: An object from `estVC` or `aicVC`, or an estimated variance-covariance matrix induced by relatedness and environment. - `intc`: Covariates that interact with QTL. - `numGeno`: Whether to treat numeric coding of genotypes as numeric. If true, `minorGenoFreq` will be ignored. - `test`: "None", "F" or "LRT". - `minorGenoFreq`: Specify the minimum tolerable minor genotype frequency at a scanning locus if `gdat` is used. - `rmv`: A logical variable. If true, then the scanning locus will be skipped if the minor genotype frequency at the locus is smaller than `minorGenoFreq`. Otherwise, the scanning process will stop and return with NULL if any loci have a genotype frequency smaller than `minorGenoFreq`. ## Details The test at a scanning locus under the null hypothesis of no QTL effect is performed by conditioning on the polygenic genetic variance-covariance. Normality is assumed for the random effects. It is possible to extend the Haley-Knott approach to multiple-allelic cases under the assumption that allelic effects are all additive. Then, `prdat` should be provided and be of class "addEff". ## Returns A list with at least the following components: - **F or LRT**: the F-test or likelihood ratio test (LRT) statistic at the SNP (marker) if `test` is "F" or otherwise - **pval**: P-value at the snp (marker) if `test` is "F" or "LRT" - **v**: Variation explained by the SNP (marker) - **parameters**: Estimated parameters at all scanning loci, including additive effect `a` and dominance effect `d` if `prdat` is not NULL ## References Haley, C. S., and S. A. Knott (1992). A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity 69: 315-324. ## See Also `genoImpute` and `genoProb`. ## Examples ```r data(miscEx) ## Not run: # impute missing genotypes pheno<- pdatF8[!is.na(pdatF8$bwt) & !is.na(pdatF8$sex),] ii<- match(rownames(pheno), rownames(gdatF8)) geno<- gdatF8[ii,] ii<- match(rownames(pheno), rownames(gmF8$AA)) v<- list(A=gmF8$AA[ii,ii], D=gmF8$DD[ii,ii]) # estimate variance components o<- estVC(y=pheno$bwt, x=pheno$sex, v=v) # impute missing genotypes gdtmp<- genoImpute(geno, gmap=gmapF8, gr=8, na.str=NA, msg=FALSE) # genome scan and plotting lrt<- scanOne(y=pheno$bwt, x=pheno$sex, gdat=gdtmp, vc=o) lrt plot(lrt,gmap=gmapF8) # Haley-Knott method gdtmp<- geno; unique(unlist(gdtmp)) gdtmp<- replace(gdtmp,is.na(gdtmp),0) prDat<- genoProb(gdat=gdtmp, gmap=gmapF8, gr=8, method="Haldane", msg=TRUE) pv.hk<- scanOne(y=pheno$bwt, intc=pheno$sex, prdat=prDat, vc=o, test="F") pv.hk plot(pv.hk, gmap=gmapF8) # assume additive allelic effects class(prDat)<- c(class(prDat), "addEff") lrt.hk<- scanOne(y=pheno$bwt, intc=pheno$sex, prdat=prDat, vc=o) lrt.hk ## End(Not run) ```

scanOne function