View source: R/nudge.plot.comp.R
nudge.plot.comp | R Documentation |
Plot each estimated individual components of NUDGE model
(mixture of uniform and 1-normal) fitted using nudge.fit
.
nudge.plot.comp(data, obj, new.plot = TRUE, legpos = NULL, xlim = NULL, ylim = NULL, xlab = NULL, ylab = NULL, main = NULL, lwd = NULL, ...)
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 |
new.plot |
an R list of vector of normalized intensities (counts). Each object can correspond to particular chromosome that one want to fit. |
legpos |
optional vector of (x,y) location for the legend position |
xlim |
optional x-axis limit (see |
ylim |
optional y-axis limit (see |
xlab |
optional x-axis label (see |
ylab |
optional y-axis label (see |
main |
optional plot title (see |
lwd |
optional line width for lines in the plot (see |
... |
additional graphical arguments to be passed to methods (see |
The components representing differential data are denoted by asterisk (*) symbol on the plot legend.
nudge.plot.mix
, inudge.plot.comp
,
nudge.plot.fit
, nudge.plot.qq
,
DIME.plot.fit
, gng.plot.fit
.
library(DIME); # generate simulated datasets with underlying uniform and 1-normal components set.seed(1234); N1 <- 1500; N2 <- 500; rmu <- c(1.5); rsigma <- c(1); rpi <- c(.10,.90); a <- (-6); b <- 6; chr1 <- c(-runif(ceiling(rpi[1]*N1),min = a,max =b), rnorm(ceiling(rpi[2]*N1),rmu[1],rsigma[1])); chr4 <- c(-runif(ceiling(rpi[1]*N2),min = a,max =b), rnorm(ceiling(rpi[2]*N2),rmu[1],rsigma[1])); # analyzing chromosome 1 and 4 data <- list(chr1,chr4); # fit NUDGE model with maximum iterations = 20 set.seed(1234); bestNudge <- nudge.fit(data, max.iter=20); # plot individual components of NUDGE nudge.plot.comp(data,bestNudge);
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