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MineICA (version 1.12.0)

Analysis of an ICA decomposition obtained on genomics data

Description

The goal of MineICA is to perform Independent Component Analysis (ICA) on multiple transcriptome datasets, integrating additional data (e.g molecular, clinical and pathological). This Integrative ICA helps the biological interpretation of the components by studying their association with variables (e.g sample annotations) and gene sets, and enables the comparison of components from different datasets using correlation-based graph.

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Version

Version

1.12.0

License

GPL-2

Maintainer

Anne Biton

Last Published

February 15th, 2017

Functions in MineICA (1.12.0)

annot2Color

Association of a colour with each annotation level
MineICAParams

Class to contain parameters for the analysis of an ICA decomposition.
clusVarAnalysis

Tests association between clusters of samples and variables
runAn

Run analysis of an IcaSet object
nbOccByGeneInComp

nbOccByGeneInComp
selectFeatures_IQR

Selection of features based on their IQR
nbOccInComp_simple

nbOccInComp_simple
addGenesToGoReport

Add Symbol IDs to hyperGTest results
plotMclust

plotMix

plotCorGraph

Plots graph using
plotPosOneAnnotInComp_ggplot

Tests if groups of samples are differently distributed on the components and do the corresponding plots.
quantVarAnalysis

Correlation between variables and components.
annotFeatures

Annotation of features using an annotation package
cor2An

Correlation between two matrices
getProj

Extract projection values
Alist

selectContrib

Select contributing features/genes
buildMineICAParams

Creates an object of class MineICAParams
build_sortHeatmap

Build the heatmap matrices
icaSetCarbayo

IcaSet-object containing a FastICA decomposition of gene expression microarrray-based data of bladder cancer samples.
icaSetRiester

IcaSet-object containing a FastICA decomposition of gene expression microarrray-based data of bladder cancer samples.
icaSetStransky

IcaSet-object containing a FastICA decomposition of gene expression microarrray-based data of bladder cancer samples.
wilcoxOrKruskalOnA

Comparison of distributions of sample groups
plot_heatmapsOnSel

Plot heatmap associated with each component
A

Retrieve and set Source S and Mixing matrix A from IcaSet
correl2Comp

correl2Comp
relativePath

Relative path
clusterSamplesByComp_multiple

Cluster samples from an IcaSet
writeProjByComp

writeProjByComp
plotPosAnnotInComp

Histograms of sample contributions for each annotation level
writeGostatsHtmltable

Writes enrichment results in a HTML file
plotDens2classInComp_plotOnly

compareGenes

Union and intersection of contributing genes
annotFeaturesWithBiomaRt

Annotation of features using biomaRt
plotPosOneAnnotLevInComp_ggplot

plotPosSamplesInComp

Histograms of sample subsets
writeHtmlResTestsByAnnot

Tests if groups of samples are differently distributed on the components according and do the corresponding plots.
annotInGene

Features annotation of an object of class IcaSet.
IcaSet

Class to Contain and Describe an ICA decomposition of High-Throughput Data.
hypergeoAn

runICA

Run of fastICA and JADE algorithms
clusterSamplesByComp

Cluster samples from an IcaSet
getSdExpr

getSdExpr
doEnrichment

Runs enrichment analysis of contributing genes
mergeGostatsResults

Merge enrichment results obtained for different databases into one file per component.
indComp

Retrieve and set component labels, indices, and witness genes from IcaSet
runCompareIcaSets

runCompareIcaSets
runEnrich

annotReciprocal

annotReciprocal
hgOver

Output of hyperGtest
icaSetKim

IcaSet-object containing a FastICA decomposition of gene expression microarrray-based data of bladder cancer samples.
plotAllMix

Plots the Gaussian fitted by Mclust on several numeric vectors
nbOccInComp

Select components the features contribute to
plotDensOneAnnotInAllComp

Tests if groups of samples are differently distributed on the components and do the corresponding plots.
selectWitnessGenes

selectWitnessGenes
writeRnkFiles

Write rnk files containing gene projections
clusterFastICARuns

Run of fastICA and JADE algorithms
dat

Retrieve and set data from IcaSet
annotCarbayo

Carbayo annotation data
dataCarbayo

Carbayo expression data
annotFeaturesComp

Features annotation
compareAn2graphfile

compareAn2graphfile
qualVarAnalysis

Tests association between qualitative variables and components.
readS

read S
readA

read A
writeGenes

Description of features using package biomaRt.
buildIcaSet

Slist

compareAn

Comparison of IcaSet objects using correlation
getComp

Retrieve feature and sample values on a component stored in an IcaSet object.
nodeAttrs

Generate node attributes
plotDensAllAnnotInAllComp

Tests if groups of samples are differently distributed on the components according and do the corresponding plots.