synbreed (version 0.12-6)

plotGenMap:

Description

A function to visualize low and high-density marker maps.

Usage

# S3 method for GenMap
plot(x, dense = FALSE, nMarker = TRUE, bw=1,
                      centr=NULL, file=NULL, fileFormat="pdf",...)

plotGenMap(map, dense = FALSE, nMarker = TRUE, bw=1, centr=NULL, file=NULL, fileFormat="pdf",...)

Arguments

x
object of class GenMap, i. e. the map object in a gpData-object
map
object of class gpData with object map or a data.frame with columns 'chr' (specifying the chromosome of the marker) and 'pos' (position of the marker within chromosome measured with genetic or physical distances)
dense
logical. Should density visualization for high-density genetic maps be used?
nMarker
logical. Print number of markers for each chromosome?
bw
numeric. Bandwidth to use for dense=TRUE to control the resolution (default = 1 [map unit]).
centr
numeric vector. Positions for the centromeres in the same order as chromosomes in map. If "maize", centromere positions of maize in Mbp are used (according to maizeGDB, version 2).
file
Optionally a path to a file where the plot is saved to
fileFormat
character. At the moment two file formats are supported: pdf and png. Default is "pdf".
further graphical arguments for function plot

Value

Plot of the marker positions within each chromosome. One chromosome is displayed from the first to the last marker.

Details

In the low density plot, the unique positions of markers are plotted as horizontal lines. In the high-density plot, the distribution of the markers is visualized as a heatmap of density estimation together with a color key. In this case, the number of markers within an interval of equal bandwidth bw is counted. The high density plot is typically useful if the number of markers exceeds 200 per chromosome on average.

See Also

create.gpData

Examples

Run this code
## Not run: ------------------------------------
# library(synbreedData)
# # low density plot
# data(maize)
# plotGenMap(maize)
# 
# # high density plot
# data(mice)
# plotGenMap(mice,dense=TRUE,nMarker=FALSE)
## ---------------------------------------------

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