plot_PatternRuns {detectRUNS} | R Documentation |
Function to plot the sum of run lengths (or the average run length) per individual against the average number of runs per individual. Points can be differentially coloured by group/population. This plot can be useful to identify patterns in the distribution of runs in different groups (e.g. few long runs vs many short runs)
plot_PatternRuns(runs, mapFile, method = c("sum", "mean"),
outputName = NULL, savePlots = FALSE, plotTitle = NULL)
runs |
a data.frame with runs per individual (group, id, chrom, nSNP, start, end, length) |
mapFile |
map file (.map) file path |
method |
"sum" or "mean" of run lengths per individual sample |
outputName |
title prefix (the base name of graph, if savePlots is TRUE)#' |
savePlots |
should plots be saved out to files or plotted in the graphical terminal (default)? |
plotTitle |
title in plot (default NULL) |
plot of number of runs vs run-length sum/mean per individual sample
# getting map and ped paths
genotypeFile <- system.file("extdata", "Kijas2016_Sheep_subset.ped", package = "detectRUNS")
mapFile <- system.file("extdata", "Kijas2016_Sheep_subset.map", package = "detectRUNS")
# calculating runs of Homozygosity
## Not run:
# skipping runs calculation
runs <- slidingRUNS.run(genotypeFile, mapFile, windowSize = 15, threshold = 0.1, minSNP = 15,
ROHet = FALSE, maxOppositeGenotype = 1, maxMiss = 1, minLengthBps = 100000, minDensity = 1/10000)
## End(Not run)
# loading pre-calculated data
runsFile <- system.file("extdata", "Kijas2016_Sheep_subset.sliding.csv", package="detectRUNS")
runsDF <- readExternalRuns(inputFile = runsFile, program = 'detectRUNS')
plot_PatternRuns(runs = runsDF, mapFile = mapFile, method = 'sum')
plot_PatternRuns(runs = runsDF, mapFile = mapFile, method = 'mean')