sliceone: Genome Slice to detect QTL for Phenotypic Trait
In fboehm/qtlbim: QTL Bayesian Interval Mapping

Description Usage Arguments Details Value Author(s) References See Also Examples

This method extracts iteration diagnostics and mainloci from the qb object and returns a data frame (of class qb.sliceone). Generic summary and plot can be used for display.

qb.sliceone(qbObject, slice, epistasis = TRUE, scan, type.scan, covar,
  adjust.covar, chr, sum.scan = "yes", min.iter = 1,
  aggregate = TRUE, smooth = 3, weight = c("sqrt","count","none","atten","ratten"),
  split.chr, center.type = c("mode","mean","scan"), verbose = FALSE, ...)
## S3 method for class 'qb.sliceone'
summary(object, chr, ...)
## S3 method for class 'qb.sliceone'
print(x, ...)
## S3 method for class 'qb.sliceone'
plot(x, ..., scan, auto.par = TRUE)

`qbObject`	An object of class `qb`.
`object`	Object of class `qb.sliceone`.
`x`	Object of class `qb.sliceone`.
`slice`	Chromosomes to slice upon.
`epistasis`	If `TRUE` then information about epistasis is included.
`scan`	Vector of diagnostics to scan (see below).
`type.scan`	Type of scan; default is "heritability" (see below).
`covar`	Covariate(s) to include; default is `seq(nfixcov)` where `nfixcov` is taken from `qb.data`. Set to 0 to exclude any covariates.
`adjust.covar`	Adjustments to covariates. Default is `NA`, which adjusts by covariate mean values. Values are assumed to be in order of fixed covariates.
`chr`	Chromosomes to subset on if not `NULL`.
`sum.scan`	Sum over `scan` diagnostics if "yes" or "only"; only report `sum` if "only".
`min.iter`	Include only samples at loci if minimum number of iterations is at least `min.iter`; default is to include all (`min.iter` = 1).
`aggregate`	Aggregate effects into main, epis, gbye if `TRUE`.
`smooth`	Degree of nearest neighbor smoothing to determine maxima.
`weight`	Weights to use for nearest neighbor smoothing. `sqrt` is square root of count per locus. Used only if `smooth` > 0.
`split.chr`	Split summary by multiple QTL per chromosome (see details for `plot.qb.scanone`).
`center.type`	Method to find QTL loci. See details.
`verbose`	Give verbose feedback if `TRUE`.
`auto.par`	Automatic setting of plot parameters for multiple plots if `TRUE`.
`...`	Arguments to be passed along.

All arguments except slice agree with qb.scanone. The slice specifies a chromosome upon which to slice, yielding a 1-D scan of what might be seen on a 2-D scan using qb.scantwo. One advantage of qb.sliceone is that you can get 2-QTL cell means for the slice chromosome and the scanned chromosomes.

The summary invokes summary.qb.scanone to summarize slice by chromosome. The plot will by default give separate plots for each slice genotype and use plot.qb.scanone to scan the chromosomes. If scan is specified for plot.qb.sliceone, then those elements will be plotted. For instance, plot(x,scan="slice") will plot the running average locus on the slice chromosome with respect to the other chromosomes.

qb.sliceone returns an object of class qb.sliceone (a data frame) containing effects selected according to type.scan and scan.

Brian S. Yandell, yandell@stat.wisc.edu

http://www.qtlbim.org

summary.qb.scanone, plot.qb.scanone

data(qbExample)

## Get profile of heritability.
temp <- qb.sliceone(qbExample, slice = 1, chr = 2:3)
summary(temp)
plot(temp)

## Get profile of cell means.
temp <- qb.sliceone(qbExample, slice = 1, chr = 2:3, type.scan = "cellmean")
summary(temp)
plot(temp)