karyoplot: Individual chromosome painting

In GHap: Genome-Wide Haplotyping

Individual chromosome painting

Description

Given smoothed ancestry predictions obtained with the ghap.ancsmooth function and the name of the indivual, an individual karyotype plot is generated.

Usage

 ghap.karyoplot(ancsmooth, ids = NULL,
                colors = NULL, chr = NULL, 
                chr.line = 10, plot.line = 25,
                chr.ang = 45, las = 0)

Arguments

ancsmooth	A list containing smoothed ancestry classifications, such as supplied by the ghap.ancsmooth function.
ids	A character vector of individual(s) to plot. If NULL all the individuals will be plotted (default = NULL).
colors	A character vector of colors to use for each ancestry label (default = NULL).
chr	A vector with the chromosome(s) to plot. If NULL, all the chromosomes will be plotted (default = NULL).
chr.line	A numeric value representing the number of chromosomes per plot line (default = 10).
plot.line	A numeric value representing the distance of horizontal guide (default = 25).
chr.ang	A numeric value representing the rotation of chromosome labels in degrees (default = 45).
las	A numeric value representing the las of y-axes (default = 0).

Details

This function takes smoothed ancestry classifications provided by the ghap.ancsmooth function and "paint" the chomosomes of one individual using the ancestry proportions. One or more individuals could be plotted in separated graph.

Author(s)

Marco Milanesi <[e-mail]>

See Also

ghap.anctrain, ghap.anctest, ghap.ancsvm, ghap.ancsmooth, ghap.ancmark, ghap.ancplot

Examples

# #### DO NOT RUN IF NOT NECESSARY ###
# 
# # Copy phase data in the current working directory
# exfiles <- ghap.makefile(dataset = "example",
#                          format = "phase",
#                          verbose = TRUE)
# file.copy(from = exfiles, to = "./")
# 
# # Load phase data
# 
# phase <- ghap.loadphase("example")
# 
# # Calculate marker density
# mrkdist <- diff(phase$bp)
# mrkdist <- mrkdist[which(mrkdist > 0)]
# density <- mean(mrkdist)
# 
# # Generate blocks for admixture events up to g = 10 generations in the past
# # Assuming mean block size in Morgans of 1/(2*g)
# # Approximating 1 Morgan ~ 100 Mbp
# g <- 10
# window <- (100e+6)/(2*g)
# window <- ceiling(window/density)
# step <- ceiling(window/4)
# blocks <- ghap.blockgen(phase, windowsize = window,
#                         slide = step, unit = "marker")
# 
# # Supervised analysis
# train <- unique(phase$id[which(phase$pop != "Cross")])
# prototypes <- ghap.anctrain(object = phase, train = train,
#                             method = "supervised")
# hapadmix <- ghap.anctest(object = phase,
#                          blocks = blocks,
#                          prototypes = prototypes,
#                          test = unique(phase$id))
# anctracks <- ghap.ancsmooth(object = phase, admix = hapadmix)
# ghap.ancplot(ancsmooth = anctracks)
# 
# ### RUN ###
# 
# # Plot karyoplot
# pure1 <- unique(phase$id[which(phase$pop == "Pure1")])
# pure2 <- unique(phase$id[which(phase$pop == "Pure2")])
# cross <- unique(phase$id[which(phase$pop == "Cross")])
# ghap.karyoplot(ancsmooth = anctracks, ids = pure1[1],
#                chr.line = 11, plot.line = 50, las=1, chr=NULL)
# ghap.karyoplot(ancsmooth = anctracks, ids = pure2[1],
#                chr.line = 11, plot.line = 50, las=1, chr=NULL)
# ghap.karyoplot(ancsmooth = anctracks, ids = cross[1],
#                chr.line = 11, plot.line = 50, las=1, chr=NULL)

GHap documentation built on July 2, 2022, 1:07 a.m.