Multi-parent population QTL analysis model using a forward regression.
mpp_forward(
pop.name = "MPP",
trait.name = "trait1",
mppData,
trait = 1,
Q.eff = "cr",
ref.par = NULL,
sum_zero = FALSE,
threshold = 4,
window = 30,
backward = TRUE,
alpha.bk = 0.05,
plot.Qprof = FALSE,
plot.gen.eff = FALSE,
CI = FALSE,
drop = 1.5,
text.size = 18,
n.cores = 1,
verbose = TRUE,
output.loc
)Return:
List containing the following items:
Number of detected QTLs.
Data.frame with QTL positions.
List containing R squared statistics of the QTL effects.
For details see QTL_R2 output section.
List of QTLs genetic effects. For details see
QTL_gen_effects output section.
If CI = TRUE, confidence interval information of
the QTLs.
Some output files are also saved at the specified location
(output.loc):
A QTL report (QTL_REPORT.txt) with: 1) the number of detected QTLs;
2) the global R squared statistics; 3) for each QTL, position information
(plus confidence interval if CI = TRUE) and estimated QTL genetic
effects per cross or parents (for details see QTL_gen_effects).
The list of QTL (QTL.txt).
The QTL R squared statistics (QTL_R2.txt) (for details see
QTL_R2).
If CI = TRUE, the QTL confidence intervals (QTL_CI.txt).
General results of the QTL detection process: number of QTLs and global adjusted and non-adjusted R squared statistics (QTL_genResults.txt).
If plot.Qprof = TRUE, the plot of the last regression run
(QTL_profile.pdf). If plot.gen.eff = TRUE, plot of the genetic
effects per cross or parents (gen_eff.pdf) with dashed lines representing
the QTL positions. For more details see plot.QTLprof
Character name of the studied population.
Default = "MPP".
Character name of the studied trait.
Default = "trait1".
An object of class mppData.
Numerical or character indicator to specify which
trait of the mppData object should be used. Default = 1.
Character expression indicating the assumption concerning
the QTL effect: 1) "cr" for cross-specific effects; 2) "par" parental
effects; 3) "anc" for an ancestral effects; 4) "biall" for a bi-allelic
effects. For more details see mpp_SIM. Default = "cr".
Optional Character expression defining the parental
allele that will be used as reference to calculate the allelic effects of
the parental model. For the ancestral model, the ancestral class containing
the reference parent will be set as reference. This option can only
be used if the MPP design is composed of a unique connected part.
Default = NULL.
Optional Logical value specifying if the QTL effect of
a parental or an ancestral model should be caculated using the sum to zero
constraint. Default = FALSE.
Numeric value representing the -log10(p-value)
threshold above which a position can be considered as significant.
Default = 4.
Numeric distance (cM) on the left and the right of a
cofactor position where it is not included in the model. Default = 30.
Logical value. If backward = TRUE,
the function performs
a backward elimination on the list of selected QTLs. Default = TRUE.
Numeric value indicating the significance level for
the backward elimination. Default = 0.05.
Logical value. If plot = TRUE,
the function will plot the QTL profile last run of the forward regression.
Default = FALSE.
Logical value. If plot.gen.eff = TRUE,
the function will save the decomposed genetic effects per cross/parent.
These results can be ploted with the function plot.QTLprof
to visualize a genome-wide decomposition of the genetic effects. This
plot will be realized on the last run of the forward regression.
This functionality is ony available for the cross-specific,
parental and ancestral models.
Default value = FALSE.
Logical value. If CI = TRUE, the function will
compute a -log10(pval) drop confidence interval for each QTL using
the QTL profile of the last iteration. Default = FALSE.
Numeric -log10(p-value) drop value at the limits of the
interval. Default = 1.5.
Numeric value specifying the size of graph axis text
elements. Default = 18.
Numeric. Specify here the number of cores you like to
use. Default = 1.
Logical value indicating if the steps of the procedure
should be printed. Default = TRUE.
Path where a folder will be created to save the results. By default the function uses the current working directory.
Vincent Garin
The function run a full MPP QTL detection using models with different possible
assumptions concerning the number of alleles at the QTL position. For more details about
the different models, see documentation of the function mpp_SIM.
The procedure is the following:
Forward regression to determine the a multi-QTL model. The function
selects successively QTL positions with -log10(pval) above the threshold.
Those positions are added as cofactors for following detection run.
The procedure stop when no more position has a -log10(pval) above the
threshold (QTL_forward).
If backward = TRUE, backward elimination on the final
list of detected QTLs.
Estimation of the QTL genetic effects and R squared statistics
(QTL_gen_effects and QTL_R2).
If CI = TRUE, confidence interval calculation
based on a CIM- (composite interval mapping removing all cofactors on the
scanned chromosome) of the last run of the forward regression.
If plot.Qprof = TRUE, plot of the last run of the forward
regression using plot.QTLprof.
If plot.gen.eff = TRUE, plot of the genetic effect distribution
along the genome of the last run of the forward regression using
plot.QTLprof.
mpp_SIM, plot.QTLprof,
QTL_gen_effects, QTL_forward, QTL_R2
if (FALSE) {
data(mppData)
# Specify a location where your results will be saved
my.loc <- "C:/.../..."
# Cross-specific model
USNAM_cr <- mpp_forward(pop.name = "USNAM", trait.name = "ULA",
mppData = mppData, plot.gen.eff = TRUE,
plot.Qprof = TRUE, CI = TRUE, output.loc = my.loc)
}
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