Starr facilitates the analysis of ChIP-chip data, in particular that of Affymetrix tiling arrays. The package provides functions for data import, quality assessment, data visualization and exploration. Furthermore, it includes high-level analysis features like association of ChIP signals with annotated features, correlation analysis of ChIP signals and other genomic data (e.g. gene expression), peak-finding with the CMARRT algorithm and comparative display of multiple clusters of ChIP-profiles. It uses the basic Bioconductor classes ExpressionSet and probeAnno for maximum compatibility with other software on Bioconductor. All functions from Starr can be used to investigate preprocessed data from the Ringo package, and vice versa. An important novel tool is the the automated generation of correct, up-to-date microarray probe annotation (bpmap) files, which relies on an efficient mapping of short sequences (e.g. the probe sequences on a microarray) to an arbitrary genome.
|Author||Benedikt Zacher, Johannes Soeding, Pei Fen Kuan, Matthias Siebert, Achim Tresch|
|Date of publication||None|
|Maintainer||Benedikt Zacher <firstname.lastname@example.org>|
backgd.sd: Background parameters (internal function)
bpmapToProbeAnno: Creating a probeAnno object
cmarrt.ma: Compute moving average statistics by incorporating the...
cmarrt.peak: Obtain bound regions for a given error rate control
correlate: Correlate the values of two named vectors
correlationPlot: correlation of ChIP signals to other data
declare.bound: Declare bound probes for a given error rate control
densityscatter: Compute density of a scatterplot
expressionByFeature: Getting expression value by feature from an ExpressionSet
fill: Fill large spaces in one profile with NA
fillNA: Fill large spaces in profiles with NA
filterGenes: Filter Features/Genes
getFeatures: Getting profiles of one annotated features with a given...
getIntensites: Get profile of anntated features from a probe mapping
getMeans: Get mean ChIP-signal over annotated features
getProfiles: Get profiles of ChIP-signal over annotated features
getProfilesByBase: Get profiles of ChIP-signal over annotated features...
getRatio: Building ratio over experiments
intersection: Get the intersection of two named vectors
kde2dplot: Compute density of a scatterplot
list2matrix: Convert profile list to matrix
makeProbeAnno: Creating a probeAnno object
makeSplines: Fit splines to profiles
mapFeatures: Map middle positions of probes to annotated features
ma.stat: Compute moving average statistics and p-values
match_ac: Exact String matching using the Aho-Corasick algorithm
normalize.Probes: Normalization of probes
plot.boxes: boxplots of experiments
plot.cmarrt: Histogram of p-values and normal QQ plots for standardized MA...
plot.Density: density plots of experiments
plot.gcBias: Visualize GC-Bias of Hybridization
plot.image: Reconstruct the array image
plot.ma: M versus A plot
plot.posBias: Bias of hybridzation, depending on base position in sequence.
plotProfiles: Plotting ChIP profiles of one or more clusters
plot.ratioScatter: Plot ratios of all possible combinations of IP and CONTROL
plot.scatter: High level scatterplot of experiments
profileplot: Vizualize clusters
rankPercentile.normalize: Rank precentile Normalization
readCelFile: Read raw intensities from CEL files
read.gffAnno: Reading gff annotation
remap: Remap reporter sequences to the genome and create a new bpmap...
RGlist2ExpressionSet: Convert an RGlist to an ExpressionSet
rm.small.peak: Remove bound regions which consist of too few probes
sameLength: Make equal length of upstream and downstream regions in a...
singleclusterplot: single cluster plot
sort.by.genomic: Pre-process the data by genomic location
substract: Substract mean or median from data
whichIn: Map positions to intervals
windowxy: Get mfcol or mfrow for a number of plots to one device
writeGFF: write ChIP-chip data to a gff file
writePosFile: Creating a pos file
writeWIG: write ChIP-chip data to a *.wig file