# Single Cell Differential Expression

## Documentation for package ‘scde’ version 2.39.0

- DESCRIPTION file

## Help Pages

scde-package | Single-cell Differential Expression (with Pathway And Gene set Overdispersion Analysis)
bwpca | Determine principal components of a matrix using per-observation/per-variable weights
clean.counts | Filter counts matrix
clean.gos | Filter GOs list
es.mef.small | Sample data
knn | Sample error model
knn.error.models | Build error models for heterogeneous cell populations, based on K-nearest neighbor cells.
make.pagoda.app | Make the PAGODA app
o.ifm | Sample error model
pagoda.cluster.cells | Determine optimal cell clustering based on the genes driving the significant aspects
pagoda.effective.cells | Estimate effective number of cells based on lambda1 of random gene sets
pagoda.gene.clusters | Determine de-novo gene clusters and associated overdispersion info
pagoda.pathway.wPCA | Run weighted PCA analysis on pre-annotated gene sets
pagoda.reduce.loading.redundancy | Collapse aspects driven by the same combinations of genes
pagoda.reduce.redundancy | Collapse aspects driven by similar patterns (i.e. separate the same sets of cells)
pagoda.show.pathways | View pathway or gene weighted PCA
pagoda.subtract.aspect | Control for a particular aspect of expression heterogeneity in a given population
pagoda.top.aspects | Score statistical significance of gene set and cluster overdispersion
pagoda.varnorm | Normalize gene expression variance relative to transcriptome-wide expectations
pagoda.view.aspects | View PAGODA output
papply | wrapper around different mclapply mechanisms
pollen | Sample data
scde | Single-cell Differential Expression (with Pathway And Gene set Overdispersion Analysis)
scde.browse.diffexp | View differential expression results in a browser
scde.edff | Internal model data
scde.error.models | Fit single-cell error/regression models
scde.expression.difference | Test for expression differences between two sets of cells
scde.expression.magnitude | Return scaled expression magnitude estimates
scde.expression.prior | Estimate prior distribution for gene expression magnitudes
scde.failure.probability | Calculate drop-out probabilities given a set of counts or expression magnitudes
scde.fit.models.to.reference | Fit scde models relative to provided set of expression magnitudes
scde.posteriors | Calculate joint expression magnitude posteriors across a set of cells
scde.test.gene.expression.difference | Test differential expression and plot posteriors for a particular gene
show.app | View PAGODA application
view.aspects | View heatmap
ViewPagodaApp | A Reference Class to represent the PAGODA application
ViewPagodaApp-class | A Reference Class to represent the PAGODA application
winsorize.matrix | Winsorize matrix