macat: MicroArray Chromosome Analysis Tool

This library contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. MACAT is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions. The functions have been tested on a publicly available data set about acute lymphoblastic leukemia (Yeoh et al.Cancer Cell 2002), which is provided in the library 'stjudem'.

AuthorBenjamin Georgi, Matthias Heinig, Stefan Roepcke, Sebastian Schmeier, Joern Toedling
Date of publicationNone
MaintainerJoern Toedling <jtoedling@yahoo.de>
LicenseArtistic-2.0
Version1.48.0

View on Bioconductor

Functions

basePairDistance Man page
buildMACAT Man page
compare.gammas Man page
compute.sliding Man page
crossvalParam Man page
demo.part Man page
discreteKernelize Man page
discretize Man page
discretizeAll Man page
discretizeAllClasses.tscores Man page
discretizeChromosome Man page
discretizeOne Man page
discretize.tscores Man page
evalParams Man page
evalScoring Man page
evaluateParameters Man page
fitkernelparams Man page
getExpressionByChromosome.MACATData Man page
getExpressionByClass.MACATData Man page
getExpressionByProbeset.MACATData Man page
getExpression.MACATData Man page
getFromDb Man page
getHtml Man page
getResults Man page
getsteps Man page
kernelize Man page
kernelizeAll Man page
kernelizeToPython Man page
kernelmatrix Man page
kernels Man page
kNN Man page
loaddatapkg Man page
Loader Man page
MACATData Man page
MACATinput Man page
maxDistances Man page
myhtml Man page
pair.distances Man page
plot.MACATevalScoring Man page
plot.MACATevP Man page
plotSliding Man page
preprocessedLoader Man page
pydata Man page
pythondata Man page
rawDataToPython Man page
rbf Man page
saveForPython Man page
scoring Man page
slidingAverageAt Man page
squaredDist Man page
stjd Man page
toPython Man page

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