CHRONOS (version 1.0.3)

scoreSubpathways: Evaluate subpathways using an interacting scorng scheme (IS) for each time point.

Description

Evaluate subpathways using an interacting scorng scheme (IS) for each time point.

Usage

scoreSubpathways(subpathways, filters, measures, parameters, miRNAinteractions)

Arguments

subpathways

Subpaths as returned from extractLinearSubpathways and extractNonLinearSubpathways.

filters

Named vector of filters used for subpathway evaluation. Values denote corresponding thresholds.

		pvalue
Statistical evaluation
measures	Structural and functional evaluation
	subScore	mRNA-mRNA interaction scoring

measures

Subpathway structural and functional aspects as returned from pathwayMeasures.

parameters

C,K,T parameters of scoring scheme.

miRNAinteractions

An edgelist of miRNA-mRNA interactions used to override downloaded interactions from miRecords.

Value

	subpathways	High ranking subpathways
	subScores	miRNA-subpathway scores
	mRNAScores	mRNA-mRNA scores for each subpathway and for each time point
	miRNAsOverSubpathway	High ranking miRNAs hitting each subpathway
	pValues	P-value of each subpathway

Details

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References

Jethava, V., Bhattacharyya, C., Dubhashi, D., & Vemuri, G. N. (2011). Netgem: Network embedded temporal generative model for gene expression data. BMC bioinformatics, 12(1), 327.

Kim,Y. et al. (2011). Principal network analysis: identification of subnetworks representing major dynamics using gene expression data. Bioinformatics, 27(3), 391-398

Examples

# Load extracted subpathways from toy data
load(system.file('extdata', 'Examples//data.RData', package='CHRONOS'))

# Import mRNA expressions
mRNAexpr <- importExpressions(data=mRNAexpr, type='mRNA', org='hsa')

# Score extracted linear subpathways
filters       <- c('subScore'=0.4)
linSubsScored <- scoreSubpathways(subpathways=linSubs, filters=filters)