mppGE_SIM: MPP GxE Simple Interval Maping

In vincentgarin/mppGxE: MPP GxE QTL analysis

MPP GxE Simple Interval Maping

Description

Computes single QTL models along the genome using different models.

Usage

mppGE_SIM(
  mppData,
  trait,
  Q.eff = "cr",
  VCOV = "CS_CSRT",
  plot.gen.eff = FALSE,
  parallel = FALSE,
  cluster = NULL,
  workspace = 8e+06
)

Arguments

mppData	An object of class mppData.
trait	Character vector specifying which traits (environments) should be used.
Q.eff	Character expression indicating the assumption concerning the QTL effects: 1) "cr" for cross-specific; 2) "par" for parental; 3) "anc" for ancestral; 4) "biall" for a bi-allelic. Default = "cr".
VCOV	VCOV Character expression defining the type of variance covariance structure used. "ID" for identity, "CSRT" for within environment cross-specific residual terms, "CS_CSRT" for compound symmetry with within environment cross-specific residual terms. Default = "CS_CSRT".
plot.gen.eff	Logical value. If plot.gen.eff = TRUE, the function will save the significance of the QTL allelic effects per cross/parent along the genome. These results can be visualized with the function plot_genEffects_GE. Default value = FALSE.
parallel	Logical value specifying if the function should be executed in parallel on multiple cores. To run the function in parallel user must provide clusters in the cluster argument. Parallelization is only available for 'ID' model. Default = FALSE.
cluster	Cluster object obtained with the function makeCluster() from the parallel package. Default = NULL.
workspace	Size of workspace for the REML routines measured in double precision words (groups of 8 bytes). The default is workspace = 8e6.

Value

Return:

SIM	Data.frame of class QTLprof. with five columns : 1) QTL marker or in between position names; 2) chromosomes; 3) interger position indicators on the chromosome; 4) positions in centi-Morgan; and 5) -log10(p-val). And if plot.gen.eff = TRUE, p-values of the cross or parental QTL allelic effects.

Author(s)

Vincent Garin

See Also

mppGE_CIM, plot_genEffects_GE

Examples

library(asreml)
library(mppR)

data(mppData_GE)

SIM <- mppGE_SIM(mppData = mppData_GE, trait = c('DMY_CIAM', 'DMY_TUM'),
                 Q.eff = 'par', plot.gen.eff = TRUE)

Qpos <- QTL_select(Qprof = SIM, threshold = 3, window = 50)

plot(x = SIM, QTL = Qpos)

plot_genEffects_GE(mppData = mppData_GE, nEnv = 2, EnvNames = c('CIAM', 'TUM'),
                   Qprof = SIM, Q.eff = 'par', QTL = Qpos, text.size = 14)

vincentgarin/mppGxE documentation built on June 25, 2022, 2:45 p.m.