Man pages for beyergroup/ADImpute
Adaptive Dropout Imputer (ADImpute)

ArrangeDataData trimming
CenterDataData centering
CheckArguments_ImputeArgument check to Impute()
ChooseMethodMethod choice per gene
CombineCombine imputation methods
ComputeMSEGenewiseComputation of MSE per gene
CreateArgCheckArgument check
CreateTrainDataPreparation of training data for method evaluation
DataCheck_MatrixData check (matrix)
DataCheck_NetworkData check (network)
DataCheck_SingleCellExperimentData check (SingleCellExperiment)
DataCheck_TrLengthData check (transcript length)
demo_dataSmall dataset for example purposes
demo_netSmall regulatory network for example purposes
demo_sceSmall dataset for example purposes
EvaluateMethodsImputation method evaluation on training set
GetDropoutProbabilitiesGet dropout probabilities
HandleBiologicalZerosGet dropout probabilities
ImputeDropout imputation using different methods
ImputeBaselineImpute using average expression across all cells
ImputeDrImputeUse DrImpute
ImputeNetParallelNetwork-based parallel imputation
ImputeNetworkNetwork-based imputation
ImputeNPDropoutsHelper function to PseudoInverseSolution_percell
ImputePredictiveDropoutsHelper function to PseudoInverseSolution_percell
ImputeSAVERUse SAVER
MaskDataMasking of entries for performance evaluation
MaskerPerGeneHelper mask function
network.coefficientsTranscriptome wide gene regulatory network
NormalizeRPMRPM normalization
NormalizeTPMTPM normalization
PseudoInverseSolution_percellNetwork-based parallel imputation - Moore-Penrose...
ReadDataData read
ReturnChoiceWrapper for return of EvaluateMethods()
ReturnOutWrapper for return of Impute()
SetBiologicalZerosSet biological zeros
SplitDataSelection of samples for training
transcript_lengthTable for transcript length calculations
WriteCSVWrite csv file
WriteTXTWrite txt file
beyergroup/ADImpute documentation built on Dec. 19, 2021, 8:48 a.m.