Multi-parent population QTL analysis.
mpp_proc(
pop.name = "MPP",
trait.name = "trait1",
mppData,
trait = 1,
Q.eff = "cr",
plot.gen.eff = FALSE,
thre.cof = 3,
win.cof = 50,
N.cim = 1,
window = 20,
thre.QTL = 3,
win.QTL = 20,
backward = TRUE,
alpha.bk = 0.05,
ref.par = NULL,
sum_zero = 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 cofactors positions.
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 SIM and CIM results in a text file (SIM.txt, CIM.txt).
The list of cofactors (cofactors.txt).
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).
The plot of the CIM profile (QTL_profile.pdf) with dotted vertical
lines representing the cofactors positions. 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".
Logical value. If plot.gen.eff = TRUE,
the function will save the decomposed genetic effects per cross/parent.
These results can be plotted with the function plot.QTLprof
to visualize a genome-wide decomposition of the genetic effects.
This functionality is ony available for the cross-specific,
parental and ancestral models.
Default value = FALSE.
Numeric value representing the -log10(p-value)
threshold above which a position can be peaked as a cofactor. Default = 3.
Numeric value in centi-Morgan representing the minimum
distance between two selected cofactors. Default = 50.
Numeric value specifying the number of time the CIM
analysis is repeated. Default = 1.
Numeric distance (cM) on the left and the right of a
cofactor position where it is not included in the model. Default = 20.
Numeric value representing the -log10(p-value)
threshold above which a position can be selected as QTL. Default = 3.
Numeric value in centi-Morgan representing the minimum
distance between two selected QTLs. Default = 20.
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. Terms with p-values above this value will
iteratively be removed. Default = 0.05.
Optional Character expression defining the parental
allele that will be used as reference to compute QTL effects for 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 calculated using the sum to zero
constraint. Default = FALSE.
Logical value. If CI = TRUE, the function will
compute a -log10(pval) drop confidence interval for each QTL after
calculating a CIM- profile (without cofactors on the scanned chromosome).
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 mpp_proc should
be printed. Default = TRUE.
Path where a folder will be created to save the results.
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:
Simple interval mapping (SIM) to select cofactor
(mpp_SIM).
Composite interval mapping (CIM) with selected cofactors
(mpp_CIM).
Optional backward elimination on the list of QTL
candidates (backward = TRUE) (mpp_back_elim).
Computation of the QTL genetic effects (QTL_gen_effects)
and proportion of the phenotypic variation explained by the QTLs (R squared)
(QTL_R2).
Optional QTL confidence interval computation from a CIM- profile
(excluding cofactors on the scanned chromosome) (argument CI=TRUE).
mpp_back_elim,
mpp_CIM,
mpp_perm,
mpp_SIM,
plot.QTLprof,
QTL_gen_effects,
QTL_R2
data(mppData)
# Specify a location where your results will be saved
my.loc <- tempdir()
# Cross-specific model
USNAM_cr <- mpp_proc(pop.name = "USNAM", trait.name = "ULA",
mppData = mppData, plot.gen.eff = TRUE, CI = TRUE,
verbose = FALSE, output.loc = my.loc)
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