Description Usage Arguments Details Value Author(s) References See Also Examples
These routines work in conjunction with qb.hpdone
,
qb.scantwo
, qb.sliceone
and
step.fitqtl
to infer the number, pattern and position of
QTL from MCMC samples.
1 2 3 4 5 6 7 8 9 10 11 | qb.arch(object, ...)
## Default S3 method:
qb.arch(object, chr, pos, tolerance = 10, ...)
## S3 method for class 'step.fitqtl'
qb.arch(object, main, epistasis, ...)
## S3 method for class 'qb.BestPattern'
qb.arch(object, ...)
## S3 method for class 'qb.arch'
summary(object, ...)
## S3 method for class 'qb.arch'
print(x, ...)
|
object |
Object for appropriate method: summary of object of
class |
x |
Object of class |
chr |
Vector of chromosome numbers. |
pos |
Vector of positions on chromosomes (much be same length as |
tolerance |
Minimum distance for two QTL to be considered distinct. |
main |
Vector of chromosome identifiers with only main effects. |
epistasis |
Data frame with a 2-element vector of chromosome identifiers for each epistatic pair. |
... |
Not used here. |
Extract architecture in terms of chromosomes and positions of main QTL
and identifiers of epistatic pairs of QTL. The step.fitqtl
approach is used to compare an automatic fit to a user-defined set of
main chromosomes and epistatic pairs.
qtl |
Data frame with main QTL as |
by.num |
Data frame with epistatic pairs indexed by chromosome
number, labeled |
by.chr |
List with elements |
by.set |
List of connected sets of epistatic chromosomes. |
Brian S. Yandell
http://www.qtlbim.org
step.fitqtl
, qb.sweave
, qb.best
1 2 3 4 5 6 7 8 |
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