wgaim (version 2.0-6)

outStat: A faceted ggplot of the chromosome outlier statistics or the interval blups/outlier statistics obtained from specified iteratons of wgaim.

Description

A faceted ggplot() of the chromosome outlier statistics or the interval blups/outlier statistics from specified iteratons of wgaim. The interval blups/outlier statistics appear as a trace across the genome separated by chromosomes and appropriately spaced by their cM distances.

Usage

outStat(object, intervalObj, iter = NULL, chr = NULL, statistic =
        "outlier", plot.chr = FALSE, chr.lines = FALSE)

Value

The blups or outlier statistics are plotted in a faceted ggplot()

with information of significant QTL overlayed.

Arguments

object

object of class "wgaim".

intervalObj

object of class "interval".

iter

range of integers determining which iterations will be plotted.

chr

character vector naming the subset of chromosomes to plot.

statistic

character string naming the type of diagnostic statistic to be plotted. Default is "outlier" (outlier statistics). Other option is "blups" for the scaled empirical blups calculated during each iteration.

plot.chr

logical value, if TRUE then plot chromosome outlier statistics. If FALSE then plot interval outlier statistics (see Details). Defaults to FALSE.

chr.lines

logical value, if TRUE then plot vertical lines to show separation of linkage groups. This is only useful if plot.chr = FALSE. Defaults to FALSE.

Author

Julian Taylor

Details

If plot.chr = TRUE then outlier statistics for each chromosome are plotted in separate faceted panels for specified values of chr and iter. This option requies selection="chromosome" to be set in the wgaim.asreml() call. If plot.chr = FALSE then interval blups or outlier statistics are plotted in separate faceted panels for specified values of chr and iter.

Additionally, the set of significant QTL (chromosome and interval position) are extracted from the model object and annotated on the plot in their appropriate positions in each facet panel. Graphical aesthetics, such as themes, text, font etc. can be further manipulated through the inclusion of additional overlays to the returned ggplot() object.

References

Verbyla, A. P & Taylor, J. D, Verbyla, K. L (2012). RWGAIM: An efficient high dimensional random whole genome average (QTL) interval mapping approach. Genetics Research. 94, 291-306.

Julian Taylor, Arunas Vebyla (2011). R Package wgaim: QTL Analysis in Bi-Parental Populations Using Linear Mixed Models. Journal of Statistical Software, 40(7), 1-18. URL https://www.jstatsoft.org/v40/i07/.

Verbyla, A. P., Cullis, B. R., Thompson, R (2007) The analysis of QTL by simultaneous use of the full linkage map. Theoretical and Applied Genetics, 116, 95-111.

See Also

tr.wgaim, wgaim

Examples

if (FALSE) {
# fit wgaim model

rkyld.qtl <- wgaim(rkyld.asf, intervalObj = genoRxK, merge.by = "Genotype",
                  trace = "trace.txt", na.action = na.method(x = "include"))

# plot QTL interval outlier statistics

outStat(rkyld.qtl, genoRxK, iter = 1:5)

}