fabia (version 2.18.0)

samplesPerFeature: Factor Analysis for Bicluster Acquisition: Supplies samples per feature

Description

samplesPerFeature: C implementation of samplesPerFeature.

Usage

samplesPerFeature(X,samples=0,lowerB=0.0,upperB=1000.0)

Arguments

X

the file name of the sparse matrix in sparse format.

samples

vector of samples which should be read; default = 0 (all samples)

lowerB

lower bound for filtering the inputs columns, the minimal column sum; default = 0.0.

upperB

upper bound for filtering the inputs columns, the maximal column sum; default = 1000.0.

Value

list with elements: sL (List with one element per feature: each element is a vector of samples where the feature is not zero.) nsL Vector of feature length containing number of samples having a non-zero feature value.

Details

Supplies the samples for which a feature is not zero.

The data matrix is directly scanned by the C-code and must be in sparse matrix format.

Sparse matrix format: *first line: numer of rows (the samples). *second line: number of columns (the features). *following lines: for each sample (rows) three lines with

I) number of nonzero row elements

II) indices of the nonzero row elements (ATTENTION: starts with 0!!)

III) values of the nonzero row elements (ATTENTION: floats with decimal point like 1.0 !!)

The code is implemented in C.

References

S. Hochreiter et al., ‘FABIA: Factor Analysis for Bicluster Acquisition’, Bioinformatics 26(12):1520-1527, 2010. http://bioinformatics.oxfordjournals.org/cgi/content/abstract/btq227

See Also

fabia, fabias, fabiap, spfabia, readSamplesSpfabia, samplesPerFeature, readSpfabiaResult, fabi, fabiasp, mfsc, nmfdiv, nmfeu, nmfsc, extractPlot, extractBic, plotBicluster, Factorization, projFuncPos, projFunc, estimateMode, makeFabiaData, makeFabiaDataBlocks, makeFabiaDataPos, makeFabiaDataBlocksPos, matrixImagePlot, fabiaDemo, fabiaVersion

Examples

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