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snapCGH (version 1.42.0)

Segmentation, normalisation and processing of aCGH data.

Description

Methods for segmenting, normalising and processing aCGH data; including plotting functions for visualising raw and segmented data for individual and multiple arrays.

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Version

Version

1.42.0

License

GPL

Maintainer

John Marioni

Last Published

February 15th, 2017

Functions in snapCGH (1.42.0)

IDProbes

Interactive version of genomePlot
genomePlot

Plots the genome
zero.length.distr.non.tiled

Empirical distribution of segment lengths in non-tiled regions with no copy number gains or losses
SegList-class

Segmentation States - class
zero.length.distr.tiled

Empirical distribution of segment lengths in tiled regions with no copy number gains or losses
compareSegmentations

Function for comparing segmentation methods to a known truth
readPositionalInfo

readPositionalInfo
cbind

Combine SegList Objects
runGLAD

Results of segmenting an aCGHList data object using the GLAD library
find.param.three

Yields output when there are 3 underlying states
fit.model

Fitting a heterogeneous HMM to the log2 ratios on a particular chromosome.
processCGH

Process data in an MAList
LargeDataObject-class

Large Data Object - class
Viterbi.five

A scaled Viterbi algorithm for allocating clones to one of five underlying states.
plotSegmentedGenome

Plots the genome
dim

Retrieve the Dimensions of an RGList, MAList or SegList Object
heatmapGenome

clustering and heatmap
simulateData

A function for simulating aCGH data and the corresponding clone layout
removeByWeights

Remove clones based on a weights matrix
runBioHMM

This function implements the BioHMM
runTilingArray

Results of segmenting an MAList data object using the Picard et al algorithm found in the tilingArray library
Viterbi.two

A scaled Viterbi algorithm for allocating clones to one of two underlying states.
log2ratios

Extracting log2 ratios
filterClones

Filter clones from sample
non.zero.length.distr.tiled

Empirical distribution of segment lengths in tiled regions with copy number gains or losses
zoomChromosome

Interactive plot of a single chromsome
chrominfo.Mb

Basic Chromosomal Information for UCSC Human Genome Assembly July 2003 freeze
find.param.five

Yields the output in a model with five underlying states
convert.output

Converts the output from the simulation to a format which can be used by segmentation schemes available within R
find.param.four

Yields output when there are 4 underlying states
imputeMissingValues

Imputing log2 ratios
find.param.one

Yields output when there is 1 underlying states
read.clonesinfo

Reading chromsome and positional information about each clone.
mergeStates

Function to merge states based on their state means
zoomGenome

Interactive plot of the whole genome
dimnames

Retrieve the Dimension Names of an RGList, MAList or SegList Object
runHomHMM

A function to fit unsupervised Hidden Markov model
non.zero.length.distr.non.tiled

Empirical distribution of segment lengths in non-tiled regions with copy number gains or losses
Viterbi.four

A scaled Viterbi algorithm for allocating clones to one of four underlying states.
Viterbi.three

A scaled Viterbi algorithm for allocating clones to one of two underlying states.
findBreakPoints

Returns the start and end of segments.
find.param.two

Yields output when there are 2 underlying states
runDNAcopy

Results of segmenting an MAList data object using the DNAcopy library