Plotting
Plot mapping results.
## S3 method for class 'scanOne' plot(x,...) plotit(lrt, cv, bychr = FALSE, chr.labels = TRUE, type = "p", lty = NULL, col = NULL, pch = NULL, cex = NULL, ...)
x |
|
lrt |
A data frame with (chr, dist, y,...) or (chr, dist, y, group,...), where "chr" represents chromosome, "dist" position on the chromosome, "y" the test statistic. |
cv |
Threshold to be drawn on the plot. |
cex |
See |
bychr |
A logical variable. If true, the plot will be displayed per chromosomes. |
chr.labels |
A logical variable. If true, the chromosome names will be drawn. |
type,lty,col,pch |
See |
... |
Other options passed to R plot function. To call |
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$DD[ii,ii]) gdat.imp<- genoImpute(geno, gmap=gmapF8, step=Inf, gr=8, na.str=NA) # estimate variance components o<- estVC(y=pheno$bwt, x=pheno$sex, v=v) # genome scan llk<- scanOne(y=pheno$bwt, x=pheno$sex, vc=o, gdat=gdat.imp) # plotting plot(llk, gmap=gmapF8) # gmap is needed # plotting in another way idx<- match(colnames(gdat.imp), gmapF8$snp) tmp<- data.frame(chr=gmapF8$chr[idx],dist=gmapF8$dist[idx],y=llk$LRT) plotit(tmp, main="Mapping Plot", xlab="Chromosome", ylab="LRT", col=as.integer(tmp$ch)%%2+2,type="p") ## End(Not run)
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