Function to explore the possible segregation type at a QTL position using the Schwarz Information Criterion
exploreQTL(
IBD_list,
Phenotype.df,
genotype.ID,
trait.ID,
linkage_group,
LOD_data,
cM = NULL,
QTLconfig = NULL,
plotBIC = TRUE,
deltaBIC = 6,
testAllele_Effects = TRUE,
log = NULL
)
List with the following items:
Linkage group of the QTL peak being explored
CentiMorgan position of the locus being explored
Vector of BIC values corresponding to elements of QTLconfig
provided for testing
Summary of the means and standard errors of groups with (+)
and without(-) the specified allele combinations for the most likely QTLconfig
if testAllele_Effects
= TRUE
(NULL
otherwise).
A one-column matrix of mean phenotype values of offspring classes, with rownames
corresponding to the genotype class. If the probability of certain genotype classes is 0 (e.g. double reduction
classes where no double reduction occurred), then the genotype mean for that class will be NA
List of IBD probabilities
A data.frame containing phenotypic values
The colname of Phenotype.df
that contains the population identifiers (F1 names) (must be a colname of Phenotype.df
)
The colname of Phenotype.df
that contains the response variable to use in the model (must be a colname of Phenotype.df
)
Numeric identifier of the linkage group being tested, based on the order of IBD_list
.
Only a single linkage group is allowed.
Output of QTLscan
function
By default NULL
, in which case the position of maximum LOD score is taken as the position of interest.
Otherwise, the cM position to be explored.
Nested list of homologue configurations and modes of action of QTL to be explored and compared, the output of segMaker
.
Note that a default List is available of all possible bi-allelic QTL if none is provided.
Each list element is itself a list with components
a vector of length at least 1, describing the proposed homologues the functional allele Q is on
Vector of same length as homs
with codes "a" for additive and "d" for dominant.
Logical, with default TRUE
- should the calculated BIC values be plotted?
Numeric, by default 6. Configurations within this distance of the minimum BIC are considered plausible.
Logical, with default TRUE
- should the effects of the different alleles be tested
using the most likely QTL configuration?
Character string specifying the log filename to which standard output should be written. If NULL
log is send to stdout.
data("IBD_4x","BLUEs.pheno","qtl_LODs.4x")
exploreQTL(IBD_list = IBD_4x,
Phenotype.df = BLUEs.pheno,
genotype.ID = "Geno",
trait.ID = "BLUE",
linkage_group = 1,
LOD_data = qtl_LODs.4x)
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