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| 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 |