AugmentSigMatrix | Make an augmented signature matrix |
buildSeed | Build a deconvolution seed matrix, add the proportional option |
buildSpilloverMat | Build a spillover matrix |
calcAcc | Calculate prediction accuracy |
clustWspillOver | Cluster with spillover |
collapseCellTypes | Collapse cell types |
estCellCounts.nPass | Deconvolve with an n-pass spillover matrix |
estCellPercent | Wrapper for deconvolution methods |
estCellPercent.DCQ | DCQ Deconvolution |
estCellPercent.DeconRNASeq | DeconRNASeq deconvolution |
estCellPercent.nnls | Non-negative least squares deconvolution |
estCellPercent.proportionsInAdmixture | WGCNA::proportionsInAdmixture deconvolution |
estCellPercent.spillOver | Estimate cell percentage from spillover |
estCellPercent.svmdecon | SVMDECON deconvolution |
findConvergenceIter | Find out at which iteration the results converge, i.e. the mean results are stable. |
getF1mcc | Get f1 / mcc |
getLM22cells | LM22 look up table |
gListFromRF | Build a gList using random forest |
hierarchicalClassify | Hierarchical Deconvolution |
hierarchicalSplit | Build hierarchical cell clusters. |
Licenses | Licenses required by Celgene legal |
LM22 | Leukocyte 22 data matrix |
loadMGSM27 | Load MGSM27 |
loadModMap | LM22 to xCell LUT |
loopTillConvergence | Loop testAllSigMatrices until convergence |
matrixToGenelist | Make a GSVA genelist |
meanResults | A meta analysis for the results from multiple iterations |
MGSM27 | Myeloma Genome Signature Matrix 27 |
missForest.par | Use parallel missForest to impute missing values. |
plotKappas | Plot condition numbers |
rankByT | Rank genes for each cell type |
remakeLM22p | Make an Augmented Signature Matrix |
scSample | Build groupSize pools according to cellIDs |
shrinkByKappa | Calculate conditions numbers for signature subsets |
shrinkSigMatrix | Shrink a signature matrix |
spillToConvergence | Spillover to convergence |
splitSCdata | Split a single cell dataset into multiple sets |
SVMDECON | Support vector machine deconvolution |
testAllSigMatrices | Generate all the signature matrices one time with the option to leave out half of the data as a test set |
weightNorm | SVMDECONV helper function |