gng.plot.comp: Plot GNG Individual Components

Description Usage Arguments Details Author(s) See Also Examples

View source: R/gng.plot.comp.R

Description

Plot each estimated individual components of GNG model (mixture of exponential and k-normal) fitted using gng.fit.

Usage

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gng.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 a particular chromosome. User can construct their own list containing only the chromosome(s) they want to analyze.

obj

a list object returned by gng.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 [email protected], with contributions from Abbas Khalili [email protected], Dustin Potter [email protected], and Shili Lin [email protected]

See Also

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

Examples

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library(DIME);
# generate simulated datasets with underlying exponential-normal components
N1 <- 1500; N2 <- 500; K <- 4; rmu <- c(-2.25,1.50); rsigma <- c(1,1); 
rpi <- c(.05,.45,.45,.05); rbeta <- c(12,10);
set.seed(1234);
chr1 <- c(-rgamma(ceiling(rpi[1]*N1),shape = 1,scale = rbeta[1]), 
  rnorm(ceiling(rpi[2]*N1),rmu[1],rsigma[1]), 
  rnorm(ceiling(rpi[3]*N1),rmu[2],rsigma[2]), 
  rgamma(ceiling(rpi[4]*N1),shape = 1,scale = rbeta[2]));
chr2 <- c(-rgamma(ceiling(rpi[1]*N2),shape = 1,scale = rbeta[1]), 
  rnorm(ceiling(rpi[2]*N2),rmu[1],rsigma[1]), 
  rnorm(ceiling(rpi[3]*N2),rmu[2],rsigma[2]), 
  rgamma(ceiling(rpi[4]*N2),shape = 1,scale = rbeta[2])); 
chr3 <- c(-rgamma(ceiling(rpi[1]*N2),shape = 1,scale = rbeta[1]), 
  rnorm(ceiling(rpi[2]*N2),rmu[1],rsigma[1]), 
  rnorm(ceiling(rpi[3]*N2),rmu[2],rsigma[2]), 
  rgamma(ceiling(rpi[4]*N2),shape = 1,scale = rbeta[2]));
# analyzing only chromosome 1 and chromosome 3
data <- list(chr1,chr3);

# Fitting a GNG model with 2-normal component
bestGng <- gng.fit(data,K=2);

# plot individual components of GNG
gng.plot.comp(data,bestGng);
# plot mixture component on top of the individual components plot
gng.plot.mix(bestGng,resolution=1000,new.plot=FALSE);

DIME documentation built on May 29, 2017, 6:25 p.m.