plot.QTLprof: plot QTL profile

In mppR: Multi-Parent Population QTL Analysis

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 QTLprof returned by the function mpp_SIM or mpp_CIM.
gen.eff	Logical. Specify the type of plot. If gen.eff = FALSE, standard QTL profile. If gen.eff = TRUE, genome-wide genetic effect plot. In that case, the QTLprof object in x must have been calculated with argument plot.gen.eff = TRUE. Default = FALSE.
mppData	An object of class mppData. Only required if gen.eff = TRUE.
Q.eff	Character expression indicating the assumption concerning the QTL effects: 1) "cr" for cross-specific; 2) "par" for parental effects; 3) "anc" for ancestral effects. Only required if gen.eff = TRUE
QTL	Optional argument. List of QTL positions. Object of class QTLlist representing a list of selected position obtained with the function QTL_select or two columns numeric matrix with the chromosome and the position in cM. These positions will be drawn on the graph. Default = NULL.
type	Character expression indicating the type of plot should be drawn: "l" for lines , "h" for vertical bar. Default = "l".
main	Title of the graph. Default = "QTL profile".
threshold	Numeric QTL significance threshold value draw on the plot. Default = 3.
text.size	Numeric value specifying the size of graph axis text elements. Default = 18.
...	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

mpp_SIM, mpp_CIM, QTL_select

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)

mppR documentation built on Jan. 6, 2023, 1:23 a.m.