TileShuffle - Detection of differentially expressed segments in tiling array data

Package information

NameTileShuffle
TitleDetection of differentially expressed segments in tiling array data
AuthorsChristian Otto, Kristin Reiche, Jörg Hackermüller
MaintainerChristian Otto <christian@bioinf.uni-leipzig.de>
DescriptionThis package contains functions for the analysis of tiling array data. It implements a statistical approach to detect expression or differential expression in terms of differences from the background distribution that avoids any intensity-related parameters. Moreover, it reduces the most dominant tiling array biases using an affinity-dependent permutation in conjunction with a windowing approach.
LicenseGPL-2
DependsR (>= 2.1.0)
Importsmulttest, affxparser, intervals, genomeIntervals, utils, Biobase, limma
SuggestsStarr

Documentation

The reference manual is available
as pdf or html.

Alternatively, you can type in R
 ?function_name
or
 help("function_name")

Download & Installation

SourceTileShuffle_0.2.0.tar.gz
Windows binaryTileShuffle_0.2.0.zip
OSX binaryTileShuffle_0.2.0.tgz

All releases

To install this package, download the latest release and install it using
 R CMD INSTALL TileShuffle_*.* [-l lib.dir]
or interactively in R by using
 install.packages(pkgs="TileShuffle_*.*", repos=NULL)

Example

The following examples should demonstrate the main functions of this package in R.
Some of the following examples require the external data of the Starr package
that includes an artificial BPMAP and CEL files in two cellular states, wt and IP.

Reading CEL file

library(TileShuffle)
## locate external data from Starr package
path <- system.file("extdata", package = "Starr")
## define Affymetrix BPMAP file for probe mapping
bpmap.filename <- file.path(path, "Scerevisiae_tlg_chr1.bpmap")
## define Affymetrix CEL files
wt.filename <- file.path(path, "wt_IP_chr1.cel")

## read CEL file of wild-type and returns data.frame
## with probe information such as genomic localization
## of probe, GC content of probe sequence, and probe intensity.
## Note that group is '' (blank) for old Affy chr21/22arrays
## while it is "Hs" for other Human, "Mm" for Mouse,
## or "Dm" for Drosophila tiling array platforms.
wt.cel <- TileReadCel(cel.filename=wt.filename,
bpmap.filename=bpmap.filename,
group="", gc=TRUE, verbose=FALSE)

## getting an overview on the reported data.frame
str(wt.cel)

par(mfrow=c(1,2))
## investigating data
## e.g. plot density of intensities
plot(density(wt.cel$intensity), main="", xlab="Intensity")
## or GC bias with three GC content bins
boxplot(wt.cel$intensity ~ cut(wt.cel$gc,
breaks=c(0,0.36,0.52,Inf),right=FALSE),
xlab="GC content", ylab="Intensity")

Reading custom-formatted files

library(TileShuffle)
## This example requires the custom-formatted files
## in the extdata folder of this package.
path <- system.file("extdata", package = "TileShuffle")
custom.filename <- file.path(path, "Scerevisiae_tlg_chr1.bpmap")
## define Affymetrix CEL files
custom.filename <- file.path(path, "custom.txt")
stopifnot(file.exists(custom.filename))

## read custom-formatted file and return data.frame
## with probe information such as genomic localization
## of probes, GC content of probe sequences, and
## probe intensity.
custom <- TileReadCustom(custom.filename=custom.filename,
gc=TRUE, verbose=FALSE)

## getting an overview on the reported data.frame
str(custom)

par(mfrow=c(1,2))
## investigating data
## e.g. plot density of intensities
plot(density(custom$intensity), main="", xlab="Intensity")
## or GC bias with three GC content bins
boxplot(custom$intensity ~ cut(custom$gc,
breaks=c(0,0.36,0.52,Inf),right=FALSE),
xlab="GC content", ylab="Intensity")

Expression analysis

library(TileShuffle)
## locate external data from Starr package
path <- system.file("extdata", package = "Starr")
## define Affymetrix BPMAP file for probe mapping
bpmap.filename <- file.path(path, "Scerevisiae_tlg_chr1.bpmap")
## define Affymetrix CEL files
wt.filename <- file.path(path, "wt_IP_chr1.cel")

## identify highly expressed segments in wild-type
## (only 100 permutations as example)
## Note that group is here '' (blank) for old Affy chr21/22 arrays
## but commonly it is "Hs" for Human, "Mm" for Mouse or "Dm" for Drosophila
TileShuffle(bpmap.filename=bpmap.filename, cel.filename=wt.filename,
input.type=2, group="", pmonly=TRUE, normalize=TRUE,
noofperms=100, winsize=200, qvalue=0.05,
gcnum=3, diff=FALSE, output.filename="wt_high.bed",
zscore.filename="wt_high_zscore.bed", verbose=FALSE)

An example for the identification of highly and differentially expressed segments
can be found in the reference manual for the function TileShuffle.

Expression analysis (non-interactive)

To run the analysis entirely non-interactive (directly from command line),
you may consider using the .R file: TileShuffleCMD.R
It executes the function TileShuffle with the given command line arguments.

For further information on the command line parameters, type
 Rscript TileShuffleCMD.R -h

Note that the TileShuffle package must already be installed.

Bugfix of affxparser package

Due to a reported but not yet fixed bug in the affxparser package on non-windows platforms,
the function readBPMAP leaks memory and may cause the following error.
 Unable to read file: filename.bpmap, is it a BPMAP file?

In this case, please download and install one of the following bugfixed version of the affxparser package.

affxparser_1.24.0_fixed.tar.gz
affxparser_1.22.1_fixed.tar.gz
affxparser_1.20.0_fixed.tar.gz
affxparser_1.18.0_fixed.tar.gz

Contact

If you have any further questions, complaints, or bug reports, please mail to christian (at) bioinf (dot) uni-leipzig (dot) de.