summary.qb.scanone {qtlbim} | R Documentation |
Summary of a qb.scanone object.
## S3 method for class 'qb.scanone': summary(object, chr, threshold = 0, sort = "no", smooth = 3, n.qtl = 0.05, min.iter, ...) ## S3 method for class 'qb.scantwo': summary(object, chr, threshold = 0, sort = "no", which.pos = "upper", min.iter, refine = FALSE, width = 10, smooth = 3, n.qtl = 0.05, ...)
object |
A qb.scanone object. |
chr |
Chromosomes to include in summary (must be integers for now). |
threshold |
Threshold(s) for inclusion in summary (see below). |
sort |
Sort by selected column of object ("no" indicates
sort by chromosome ). |
which.pos |
Base position estimate on this summary for maximal
statistics such as LOD . |
min.iter |
Minimum number of iterations included at each position
(default gleaned from object ). |
refine |
Refine estimates if TRUE . |
width |
Window width for refinement. |
smooth |
Degree of nearest neighbor smoothing to determine maxima. |
n.qtl |
Minimum number of estimated QTL per chromosome or chromosome pair. |
... |
Not used. |
These summary method report estimates by
chromosome (or chromosome pair) at the maximum poster. Threshold can be
used to condense summary to a subset of chromosomes (or chromosome
pairs). Threshold is a
vector with names corresponding to a subset of column names of
object
. Positive threshold values select chromosomes where that
column average is above given value; negative threshold values select
chromosomes with mean value within that value of the maximum across
chromosomes. Thresholding is inclusive rather than exclusive.
It can be helpful to use summary.qb.scanone as an initial screen of
chromosomes worth a further look. Since marginal summaries can include
effects of multiple QTL and epistasis. Subsets based on 1-D scans can be
used for 2-D subsequent screens. See demo(qb.qb.scan.tour)
for an
example.
Matrix with chromosome chr
, estimated position pos
(or chromosome pairschr1
and chr2
and two columns for
pos1
and pos2
in the case of summary.qb.scantwo
) and
means or modes of each column of object
. Means are weighted by number of
MCMC sample iterations.
Brian S. Yandell, yandell@stat.wisc.edu
temp <- qb.scanone(qbExample) summary(temp, threshold = c(sum=15), sort = "sum") temp <- qb.scantwo(qbExample) summary(temp, threshold = c(upper=3), sort = "upper")