plotPXG | R Documentation |
Plot the phenotype values versus the genotypes at a marker or markers.
plotPXG(x, marker, pheno.col=1, jitter=1, infer=TRUE,
pch, ylab, main, col, ...)
x |
An object of class |
marker |
Marker name (a character string; can be a vector). |
pheno.col |
Column number in the phenotype matrix which should be used as the phenotype. One may also give a character string matching a phenotype name. Finally, one may give a numeric vector of phenotypes, in which case it must have the length equal to the number of individuals in the cross, and there must be either non-integers or values < 1 or > no. phenotypes; this last case may be useful for studying transformations. |
jitter |
A positive number indicating how much to spread out the points horizontally. (Larger numbers correspond to greater spread.) |
infer |
If TRUE, missing genotypes are filled in with a single random imputation and plotted in red; if FALSE, only individuals typed at the specified marker are plotted. |
pch |
Plot symbol. |
ylab |
Label for y-axis. |
main |
Main title for the plot. If missing, the names of the markers are used. |
col |
A vector of colors to use for the confidence intervals (optional). |
... |
Passed to |
Plots the phenotype data against the genotypes at the specified
marker. If infer=TRUE, the genotypes of individuals that were not
typed is inferred based the genotypes at linked markers via a single
imputation from sim.geno
; these points are plotted
in red. For each genotype, the phenotypic mean is plotted, with error
bars at \pm
1 SE.
A data.frame with initial columns the marker genotypes, then the phenotype data, then a column indicating whether any of the marker genotypes were inferred (1=at least one genotype inferred, 0=none were inferred).
Karl W Broman, broman@wisc.edu; Brian Yandell
find.marker
, effectplot
,
find.flanking
, effectscan
data(listeria)
mname <- find.marker(listeria, 5, 28) # marker D5M357
plotPXG(listeria, mname)
mname2 <- find.marker(listeria, 13, 26) # marker D13Mit147
plotPXG(listeria, c(mname, mname2))
plotPXG(listeria, c(mname2, mname))
# output of the function contains the raw data
output <- plotPXG(listeria, mname)
head(output)
# another example
data(fake.f2)
mname <- find.marker(fake.f2, 1, 37) # marker D1M437
plotPXG(fake.f2, mname)
mname2 <- find.marker(fake.f2, "X", 14) # marker DXM66
plotPXG(fake.f2, mname2)
plotPXG(fake.f2, c(mname,mname2))
plotPXG(fake.f2, c(mname2,mname))
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