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 |