mpp_CIM | R Documentation |
Compute QTL models along the genome using cofactors representing other genetic positions for control.
mpp_CIM( mppData, trait = 1, Q.eff = "cr", cofactors = NULL, window = 20, plot.gen.eff = FALSE, n.cores = 1 )
mppData |
An object of class |
trait |
|
Q.eff |
|
cofactors |
Object of class |
window |
|
plot.gen.eff |
|
n.cores |
|
For more details about the different models, see documentation of the
function mpp_SIM
. The function returns a -log10(p-value) QTL
profile.
Return:
CIM |
|
Vincent Garin
mpp_SIM
, QTL_select
# Cross-specific effect model ############################# data(mppData) SIM <- mpp_SIM(mppData = mppData, Q.eff = "cr") cofactors <- QTL_select(Qprof = SIM, threshold = 3, window = 20) CIM <- mpp_CIM(mppData = mppData, Q.eff = "cr", cofactors = cofactors, window = 20, plot.gen.eff = TRUE) plot(x = CIM) plot(x = CIM, gen.eff = TRUE, mppData = mppData, Q.eff = "cr") # Bi-allelic model ################## cofactors <- mppData$map[c(15, 63), 1] CIM <- mpp_CIM(mppData = mppData, Q.eff = "biall", cofactors = cofactors, window = 20) plot(x = CIM, type = "h")
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