Methods for Single-Cell RNA-Seq Data Analysis

bootstrapCluster | Assess cluster stability by bootstrapping |

buildSNNGraph | Build a nearest-neighbor graph |

cleanSizeFactors | Clean size factors |

clusterModularity | Compute the cluster-wise modularity |

clusterPurity | Evaluate cluster purity |

clusterSNNGraph | Wrappers for graph-based clustering |

coassignProb | Compute coassignment probabilities |

combineBlocks | Combine blockwise statistics |

combineMarkers | Combine pairwise DE results into a marker list |

combinePValues | Combine p-values |

combineVar | Combine variance decompositions |

computeSpikeFactors | Normalization with spike-in counts |

computeSumFactors | Normalization by deconvolution |

convertTo | Convert to other classes |

correlateGenes | Per-gene correlation statistics |

correlateNull | Build null correlations |

correlatePairs | Test for significant correlations |

createClusterMST | Minimum spanning trees on cluster centroids |

cyclone | Cell cycle phase classification |

decideTestsPerLabel | Decide tests for each label |

defunct | Defunct functions |

denoisePCA | Denoise expression with PCA |

DM | Compute the distance-to-median statistic |

doubletCells | Detect doublet cells |

doubletCluster | Detect doublet clusters |

doubletRecovery | Recover intra-sample doublets |

findMarkers | Find marker genes |

fitTrendCV2 | Fit a trend to the CV2 |

fitTrendPoisson | Generate a trend for Poisson noise |

fitTrendVar | Fit a trend to the variances of log-counts |

gene_selection | Gene selection |

getClusteredPCs | Use clusters to choose the number of PCs |

getMarkerEffects | Get marker effect sizes |

getTopHVGs | Identify HVGs |

getTopMarkers | Get top markers |

logBH | BH correction on log-p-values |

modelGeneCV2 | Model the per-gene CV2 |

modelGeneCV2WithSpikes | Model the per-gene CV2 with spike-ins |

modelGeneVar | Model the per-gene variance |

modelGeneVarByPoisson | Model the per-gene variance with Poisson noise |

modelGeneVarWithSpikes | Model the per-gene variance with spike-ins |

multiMarkerStats | Combine multiple sets of marker statistics |

pairwiseBinom | Perform pairwise binomial tests |

pairwiseTTests | Perform pairwise t-tests |

pairwiseWilcox | Perform pairwise Wilcoxon rank sum tests |

pseudoBulkDGE | Quickly perform pseudo-bulk DE analyses |

pseudoBulkSpecific | Label-specific pseudo-bulk DE |

quickCluster | Quick clustering of cells |

quickPseudotime | Quick MST-based pseudotime |

quickSubCluster | Quick and dirty subclustering |

sandbag | Cell cycle phase training |

scaledColRanks | Compute scaled column ranks |

summaryMarkerStats | Summary marker statistics |

testLinearModel | Hypothesis tests with linear models |

testPseudotime | Test for differences along pseudotime |

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