plot.cmarrt: Histogram of p-values and normal QQ plots for standardized MA...

In Starr: Simple tiling array analysis of Affymetrix ChIP-chip data

Description

Plot the histograms of p-values and normal QQ plots under correlation structure and independence.

Usage

plotcmarrt(cmarrt.ma, freq=FALSE)

Arguments

cmarrt.ma	output object from cmarrt.ma.
freq	see ?hist

Details

Diagnostic plots for comparing the distribution of standardized MA statistics under correlation and independence.

Value

Histogram of p-values and normal QQ plots under correlation structure and independence.

Note

If the normal quantile-quantile plot deviates from the reference line for unbound probes, this indicates that Gaussian approximation is not suitable for analyzing this data.

Author(s)

Pei Fen Kuan, Adam Hinz

References

P.F. Kuan, H. Chun, S. Keles (2008). CMARRT: A tool for the analysiz of ChIP-chip data from tiling arrays by incorporating the correlation structure. Pacific Symposium of Biocomputing13:515-526.

See Also

cmarrt.ma,qqnorm

Examples

# dataPath <- system.file("extdata", package="Starr")
# bpmapChr1 <- readBpmap(file.path(dataPath, "Scerevisiae_tlg_chr1.bpmap"))

# cels <- c(file.path(dataPath,"Rpb3_IP_chr1.cel"), file.path(dataPath,"wt_IP_chr1.cel"), 
# 	file.path(dataPath,"Rpb3_IP2_chr1.cel"))
# names <- c("rpb3_1", "wt_1","rpb3_2")
# type <- c("IP", "CONTROL", "IP")
# rpb3Chr1 <- readCelFile(bpmapChr1, cels, names, type, featureData=TRUE, log.it=TRUE)

# ips <- rpb3Chr1$type == "IP"
# controls <- rpb3Chr1$type == "CONTROL"

# rpb3_rankpercentile <- normalize.Probes(rpb3Chr1, method="rankpercentile")
# description <- c("Rpb3vsWT")
# rpb3_rankpercentile_ratio <- getRatio(rpb3_rankpercentile, ips, controls, description, fkt=median, featureData=FALSE)

# probeAnnoChr1 <- bpmapToProbeAnno(bpmapChr1)
# peaks <- cmarrt.ma(rpb3_rankpercentile_ratio, probeAnnoChr1, chr=NULL, M=NULL,250,window.opt='fixed.probe')

# plotcmarrt(peaks)

Starr documentation built on April 28, 2020, 7:52 p.m.