inudge.plot.comp: Plot iNUDGE Individual Components

In DIME: Differential Identification using Mixture Ensemble

Plot iNUDGE Individual Components

Description

Plot each estimated individual components of iNUDGE model (mixture of uniform and k-normal) fitted using inudge.fit.

Usage

inudge.plot.comp(data, obj, new.plot = TRUE, legpos = NULL, xlim = NULL,
  ylim = NULL, xlab = NULL, ylab = NULL, main = NULL, lwd = NULL,...)

Arguments

data	an R list of vector of normalized intensities (counts). Each element can correspond to particular chromosome. User can construct their own list containing only the chromosome(s) they want to analyze.
obj	a list object returned by inudge.fit function.
new.plot	optional logical variable on whether to create new plot.
legpos	optional vector of (x,y) location for the legend position
xlim	optional x-axis limit (see par).
ylim	optional y-axis limit (see par).
xlab	optional x-axis label (see par).
ylab	optional y-axis label (see par).
main	optional plot title (see par).
lwd	optional line width for lines in the plot (see par).
...	additional graphical arguments to be passed to methods (see par).

Details

The components representing differential data are denoted by asterisk (*) symbol on the plot legend.

Author(s)

Cenny Taslim [e-mail], with contributions from Abbas Khalili [e-mail], Dustin Potter [e-mail], and Shili Lin [e-mail]

See Also

inudge.plot.mix, inudge.plot.comp, inudge.plot.fit, inudge.plot.qq, DIME.plot.fit, gng.plot.fit.

Examples

library(DIME);
# generate simulated datasets with underlying uniform and 2-normal distributions
set.seed(12);
N1 <- 1500; N2 <- 500; rmu <- c(-2.25,1.5); rsigma <- c(1,1); 
rpi <- c(.10,.45,.45); a <- (-6); b <- 6; 
chr4 <- list(c(-runif(ceiling(rpi[1]*N1),min = a,max =b),
  rnorm(ceiling(rpi[2]*N1),rmu[1],rsigma[1]), 
  rnorm(ceiling(rpi[3]*N1),rmu[2],rsigma[2])));
chr9 <- list(c(-runif(ceiling(rpi[1]*N2),min = a,max =b),
  rnorm(ceiling(rpi[2]*N2),rmu[1],rsigma[1]), 
  rnorm(ceiling(rpi[3]*N2),rmu[2],rsigma[2])));
# analyzing chromosome 4 and 9
data <- list(chr4,chr9);

# fit iNUDGE model with 2-normal components and maximum iterations = 20
set.seed(12);
bestInudge <- inudge.fit(data, K = 2, max.iter=20);

# plot individual components of iNUDGE
inudge.plot.comp(data,bestInudge);
# plot individual components of iNUDGE an it's mixture component on the same plot
inudge.plot.mix(bestInudge,resolution=1000,new.plot=FALSE);

DIME documentation built on May 9, 2022, 5:05 p.m.