plot.QTLprof {mppR} | R Documentation |
plot QTL profile
Description
Plots the -log10(p-val) profile of a QTL analysis or a genome-wide genetic effect plot using package ggplot2.
Usage
## S3 method for class 'QTLprof'
plot(
x,
gen.eff = FALSE,
mppData,
Q.eff,
QTL = NULL,
type = "l",
main = "QTL profile",
threshold = 3,
text.size = 18,
...
)
Arguments
x |
Object of class |
gen.eff |
|
mppData |
An object of class |
Q.eff |
|
QTL |
Optional argument. List of QTL positions. Object of class
|
type |
|
main |
Title of the graph. Default = "QTL profile". |
threshold |
|
text.size |
|
... |
Ignored. |
Details
The user can plot regular QTL profiles (gen.eff = FALSE
) with
-log10(p-val) plotted against genetic position or genome-wide genetic
effects plots (gen.eff = TRUE
). To plot the genome-wide genetic
effects, the SIM and CIM QTL profile must have been computed with
plot.gen.eff = TRUE
.
The genome-wide genetic effects plots is a visualisation of the significance
of the QTL effect per cross or per parents along the genome. For a
cross-specific QTL profile (Q.eff = "cr"
): Blue color means
that the allele coming from parent A(1) increases the phenotypic value and
parent B(2) decreases it and red that parent A(1) decreases the trait and
parent B(2) increases it.
For a parental (Q.eff = "par"
) or an ancestral model
(Q.eff = "anc"
), the results are given per parents. The significance
of the effect must be interpreted as a deviation with respect to the
reference of each connected part. The reference allele is always defined as
the most frequent one. Blue (Red) colour means a signicative negative
(positive) effect with respect to the reference of the connected part.
The reference parental allele can change at each position according to the segregation rate. The parent are plotted from the top to the bottom according to the number of time their allele is set as reference. Therefore interpretation of the genetic effect plot should be done with caution. In that case, the plot should be taken as a rough indication of the signal distribution.
The colour intensity increase with the significance of the effect (p-val). The p-val are transformed into a color code (z). If p-val c [0.00001; 0.05]: z = -log10(p-val). If p-val < 0.00001: z=6. This scale allows to plot only the significant effects (p-val <= 0.05) and prevent the color scale to be determine by highly significant values (p-val < 0.00001). The colours red (positive) and blue (negative) correspond to the sign of the QTL effect.
For both type of plot, the user can pass a list of cofactors or QTL position
to the argument QTL
. These positions will be drawn on the graph using
dotted lines.
Author(s)
Vincent Garin
See Also
Examples
data(mppData)
SIM <- mpp_SIM(mppData = mppData)
QTL <- QTL_select(SIM)
plot(x = SIM, QTL = QTL)
SIM <- mpp_SIM(mppData = mppData, Q.eff = "cr", plot.gen.eff = TRUE)
QTL <- QTL_select(SIM)
plot(x = SIM, gen.eff = TRUE, mppData = mppData, Q.eff = "cr", QTL = QTL)