# Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

## Documentation for package ‘M3Drop’ version 1.36.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

bg__add_model_to_plot | Make M3Drop Plots
bg__calc_variables | Calculate Gene Variables
bg__default_mean2disp | Mean to Dispersion
bg__dropout_plot_base | Make M3Drop Plots
bg__expression_heatmap | Plot Heatmap of Gene Expression
bg__filter_cells | Filter Expression Data
bg__fitdispersion | Perform Traditional Differential Expression
bg__fit_gamma | Fit Gamma Distribution
bg__fit_logistic | Fit functions to the dropouts vs expression distribution.
bg__fit_MM | Fit functions to the dropouts vs expression distribution.
bg__fit_size_to_var | Fit gene-specific dispersion
bg__fit_ZIFA | Fit functions to the dropouts vs expression distribution.
bg__get_extreme_residuals | Get outliers from MM curve.
bg__get_mean2disp | Perform Traditional Differential Expression
bg__get_stats | Calculate Simulation Statistics
bg__highlight_genes | Make M3Drop Plots
bg__horizontal_residuals_MM_log10 | Calculate Horizontal Residuals
bg__m3dropTraditionalDE | Perform Traditional Differential Expression
bg__m3dropTraditionalDEShiftDisp | Perform Traditional Differential Expression
bg__MakeSimData | Make Simulated Data
bg__MakeSimDE | Make Simulated Data
bg__MakeSimDVar | Make Simulated Data
bg__MakeSimHVar | Make Simulated Data
bg__nbumiGroupDE | Perform Traditional Differential Expression
bg__shift_size | Shift Size Parameter
bg__test_DE_K_equiv | Differentially Expressed Genes.
bg__var_vs_drop | Variance vs Dropout Rate
BrenneckeGetVariableGenes | Identify Highly Variable Genes
Consensus_FS | Consensus Feature Selection
corFS | Other Feature Selection Methods
giniFS | Other Feature Selection Methods
irlbaPcaFS | Other Feature Selection Methods
M3DropCleanData | Filter Expression Data
M3DropConvertData | Convert Data to be suitable for M3Drop
M3DropDropoutModels | Fit functions to the dropouts vs expression distribution.
M3DropExpressionHeatmap | Plot Heatmap of Gene Expression
M3DropFeatureSelection | Differentially Expressed Genes.
M3DropGetExtremes | Get outliers from MM curve.
M3DropGetHeatmapClusters | Extracts clusters/ordered names from heatmap output
M3DropGetHeatmapNames | Extracts clusters/ordered names from heatmap output
M3DropGetMarkers | Identify marker genes
M3DropSimulationTrifecta | Make Simulated Data from a provided scRNASeq dataset.
M3DropTestShift | Test for horizontal shift.
M3DropThreeSetVenn | Three-way Venn Diagram
NBumiCheckFit | Check Fit Quality
NBumiCheckFitFS | Check Fit Quality
NBumiCoexpression | Variance-based Feature Selection
NBumiCompareModels | Compare negative binomial models
NBumiConvertData | Convert Data to be suitable for NBumi
NBumiConvertToInteger | Turn a matrix of expression values into integer counts
NBumiFeatureSelectionCombinedDrop | Dropout-based Feature Selection
NBumiFeatureSelectionHighVar | Variance-based Feature Selection
NBumiFitBasicModel | Fit Depth-Adjusted Negative Binomial Model
NBumiFitDispVsMean | Fit function between mean and dispersion
NBumiFitModel | Fit Depth-Adjusted Negative Binomial Model
NBumiHVG | Variance-based Feature Selection Accounting for Library Size and Sample Variance
NBumiImputeNorm | Normalized Data using the DANB model
NBumiPearsonResiduals | Calculate Pearson Residuals
NBumiPearsonResidualsApprox | Calculate Pearson Residuals
NBumiSimulationTrifecta | Make Simulated Data from a provided scRNASeq dataset.
obsolete__nbumiFeatureSelectionDropouts | Other Feature Selection Methods
obsolete__nbumiFeatureSelectionHighVarDist2Med | Other Feature Selection Methods
PoissonUMIFeatureSelectionDropouts | Dropout-based Feature Selection