plotFreqStat {aCGH} | R Documentation |
frequency plots and significance analysis
Description
The main application of this function is to plot the frequency of
changes.
Usage
plotFreqStat(aCGH.obj, resT = NULL, pheno = rep(1, ncol(aCGH.obj)),
chrominfo = human.chrom.info.Jul03,
X = TRUE, Y = FALSE,
rsp.uniq = unique(pheno),
all = length(rsp.uniq) == 1 && is.null(resT),
titles = if (all) "All Samples" else rsp.uniq,
cutplot = 0, thres = .25, factor = 2.5, ylm = c(-1, 1),
p.thres = c(.01, .05, .1), numaut = 22, onepage = TRUE,
colored = TRUE)
Arguments
aCGH.obj |
Object of class aCGH |
resT |
Data frame having the same structure as the result of
applying mt.maxT or mt.minP functions
from Bioconductor's multtest package for multiple testing.
The result is a data frame including the following 4 components:
'index', 'teststat', 'rawp' and 'adjp'.
|
pheno |
phenotype to compare. |
chrominfo |
Chromosomal information. Defaults to
human.chrom.info.Jul03
|
X |
Include X chromosome? Defaults to yes. |
Y |
Include Y chromosome? Defaults to no. |
rsp.uniq |
rsp.uniq specified the codes for the groups of
interest. Default is the unique levels of the phenotype. Not used
when all is T.
|
all |
all specifies whether samples should be analyzed by subgroups
(T) or together (F).
|
titles |
titles names of the groups to be used. Default is the unique
levels of the pheno .
|
cutplot |
only clones with at least cutplot frequency of
gain and loss are plotted.
|
thres |
thres is either a vector providing unique
threshold for each sample or a vector of the same length as number
of samples (columns in data ) providing sample-specific
threshold. If aCGH.obj has non-null sd.samples, then thres is automatically replaced by factor times madGenome of aCGH object. Clone is considered to be gained if it is above the
threshold and lost if it below negative threshold. Used for plotting
the gain/loss frequency data as well as for clone screening and for
significance analysis when threshold is TRUE.Defaults to 0.25
|
factor |
factor specifies the number by which experimental variability should be multiplied. used only when sd.samples(aCGH.obj ) is not NULL or when factor is greater than 0. Defaults to 2.5 |
ylm |
ylm vertical limits for the plot |
p.thres |
p.thres vector of p-value ciut-off to be plotted. computed
conservatively as the threshold corresponding to a given adjusted
p-value.
|
numaut |
numaut number of the autosomes |
onepage |
onepage whether all plots are to be plotted on one page or
different pages. When more than 2 groups are compared, we recommend multiple pages.
|
colored |
Is plotting in color or not? Default is TRUE. |
Examples
data(colorectal)
## Use mt.maxT function from multtest package to test
## differences in group means for each clone grouped by sex
colnames(phenotype(colorectal))
sex <- phenotype(colorectal)$sex
sex.na <- !is.na(sex)
colorectal.na <- colorectal[ ,sex.na, keep = TRUE ]
dat <- log2.ratios.imputed(colorectal.na)
resT.sex <- mt.maxT(dat, sex[sex.na], test = "t", B = 1000)
## Plot the result along the genome
plotFreqStat(colorectal.na, resT.sex, sex[sex.na],
titles = c("Male", "Female"))
## Adjust the p.values from previous exercise with "fdr"
## method and plot them
resT.sex.fdr <- resT.sex
resT.sex.fdr$adjp <- p.adjust(resT.sex.fdr$rawp, "fdr")
plotFreqStat(colorectal.na, resT.sex.fdr, sex[sex.na],
titles = c("Male", "Female"))
## Derive statistics and p-values for testing the linear association of
## age with the log2 ratios of each clone along the samples
age <- phenotype(colorectal)$age
age.na <- which(!is.na(age))
age <- age[age.na]
colorectal.na <- colorectal[, age.na]
stat.age <- aCGH.test(colorectal.na, age, test = "linear.regression", p.adjust.method = "fdr")
#separate into two groups: < 70 and > 70 and plot freqeuncies of gain and loss
#for each clone. Note that statistic plotted corresponds to linear coefficient
#for age variable
plotFreqStat(colorectal.na, stat.age, ifelse(age < 70, 0, 1), titles =
c("Young", "Old"), X = FALSE, Y = FALSE)
[Package
aCGH version 1.4.1
Index]