MIMQTL | R Documentation |
Perform QTL detection by multiple interval mapping
MIMQTL(
cross,
numeric.chr.format = FALSE,
response.in.cross = TRUE,
pheno.col = "y",
response = NULL,
method = "hk",
geno.joinmap = NULL,
phase = NULL,
threshold = NA,
nperm = 100,
alpha = c(0.05, NA),
plot = c(FALSE, FALSE),
QTL_position = NULL,
range_nb_qtl_max = seq(1:5),
nrun = 10,
additive.only = TRUE,
p2d = "",
scan2file = "",
type.CI = "LOD-1",
nb.cores = parallel::detectCores() - 2,
verbose = 0
)
cross |
object |
numeric.chr.format |
logical to indicate if chromosome names are numeric |
response.in.cross |
logical to indicate if response studied is in |
pheno.col |
character indicating column to study in |
response |
named numeric or vector for response if not in |
method |
method to detect QTL in |
geno.joinmap |
genotypes at markers in the JoinMap format, if NULL (default), no estimation of allelic effects is given |
phase |
marker phases |
threshold |
genomewide significance LOD threshold, if NA (default), is found by permutations (with nperm parameter). |
nperm |
number of permutations to be done in |
alpha |
vector of length 1 or 2 (optional) with thresholds for (1) the significance of QTL presence (based on permutations) and (2) the significance of linear regression on QTL effect, if NA, no threshold is applied and all allelic effects are kept. |
plot |
logical, default is FALSE. |
QTL_position |
matrix with genetic.distance and linkage.group as columns indicating QTL positions for plotting |
range_nb_qtl_max |
vector, default is seq(1:5) |
nrun |
integer, number of times to rerun |
additive.only |
logical, default is TRUE: no interaction between QTLs are added to the model |
p2d |
character, path to directory to save results |
scan2file |
optional path to scan2file (is added to p2d) |
type.CI |
type of confidence interval, default is "LOD-1" |
nb.cores |
number of cores |
verbose |
verbosity level (0/1/2) |
list of 3 elements: qtl.df is a data frame with QTL informations (linkage.group, position, LOD, interval.inf and interval.sup) / selected markers is a character vector for markers inside confidence interval /allelic effetcs is a data frame with a column predictor and a column effect with estimated allelic effects.
Agnes Doligez [aut], Charlotte Brault [ctbt], Timothee Flutre [ctb]
SIMQTL
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