Man pages for ctlab/ClusDec
Clustering approach to solve complete Deconvolution problem

chooseBestChoose best combination of clusters and deconvolve
clusdecAccuracyAccuracy for all combination of clusters
clusterCosineCosine simillarity clustering
collapseGenesCollapse Genes
countInsideCheck how many points are inside of given simplex
datasetLiverBrainLungGSE19830 dataset
deconvolveDeconvolution by it self
deconvolveClustersDeconvolution by given set of clusters
dimensionality_reconstructionDimensionality reconstruction
dimensionality_reductionSVD based dimensionality reduction
dim_errorOut of space error
estimateAdditiveNoiseEstimate additive noise
estimateNoiseNoise estimation
estimateSnrSignal To Noise estimation
evalClustersEvaluate accuracy of combination
fastDSAFast DSA algorithm implementation
geneMarkerStatsGet gene stats
generateMixedDataGenerate mixed data with or without noise
getDenseEndpointsgetting simplex endpoints
hingeHinge function
hyperVolumeCompute the volume of the given simplex
pairwiseDemingRegressionPairwise Deming regression fits between genes
pairwiseLinearFitPairwise linear fits between genes
plotProportionsDraw a plot of estimated proportions
point_selectionSelection of points at the ends of simplex using VCA...
point_selection_ieaSelection of points at the ends of simplex using IEA...
preprocessDatasetPreprocess Dataset
preprocessGSEPreprocess GSE Dataset
proportionsLiverBrainLungGSE19830 proportions
pureDsaDSA algorithm implementation for pure points
runDSARun DSA by clusters
sampleFromSimplexUniformlyGeneration of points uniformly distributed on k-dimensional...
simplexDensityCheck how many points are inside of given simplex
simplexEDensityCheck how many points are inside of given simplex
simplexRDensityRoot density
sisalSISAL algorithm
softNegSoft negative score
ctlab/ClusDec documentation built on Sept. 23, 2017, 10:24 p.m.