Package: monocle 2.35.0

Cole Trapnell

monocle: Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle also performs differential expression analysis, clustering, visualization, and other useful tasks on single cell expression data. It is designed to work with RNA-Seq and qPCR data, but could be used with other types as well.

Authors:Cole Trapnell

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monocle/json (API)
NEWS

# Install 'monocle' in R:
install.packages('monocle', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On BioConductor:monocle-2.35.0(bioc 3.21)monocle-2.34.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncologysequencingrnaseqgeneexpressiondifferentialexpressioninfrastructuredataimportdatarepresentationvisualizationclusteringmultiplecomparisonqualitycontrol

8.84 score 2 packages 1.4k scripts 5.5k downloads 60 mentions 61 exports 68 dependencies

Last updated 23 days agofrom:f50c2db2af. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
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R-4.5-linux-x86_64NOTENov 18 2024
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Exports:addCellTypeBEAMbranchTestbuildBranchCellDataSetcalABCscalculateMarkerSpecificitycalILRscellPairwiseDistancescellPairwiseDistances<-classifyCellsclusterCellsclusterGenescompareModelsdetectBifurcationPointdetectGenesdifferentialGeneTestdispersionTableestimate_texportCDSfitModelgenSmoothCurvesget_classic_muscle_markersimportCDSload_HSMMload_HSMM_markersload_lungmarkerDiffTablemcesApplyminSpanningTreeminSpanningTree<-newCellDataSetnewCellTypeHierarchyorderCellsplot_cell_clustersplot_cell_trajectoryplot_clustersplot_complex_cell_trajectoryplot_genes_branched_heatmapplot_genes_branched_pseudotimeplot_genes_in_pseudotimeplot_genes_jitterplot_genes_positive_cellsplot_genes_violinplot_multiple_branches_heatmapplot_multiple_branches_pseudotimeplot_ordering_genesplot_pc_variance_explainedplot_pseudotime_heatmapplot_rho_deltaplot_spanning_treereducedDimAreducedDimA<-reducedDimKreducedDimSreducedDimWreduceDimensionrelative2absresponseMatrixselectTopMarkerssetOrderingFiltervstExprs

Dependencies:BHBiobaseBiocGenericsBiocManagerbiocViewsbitopscliclustercolorspacecombinatcpp11DDRTreedplyrfansifarverfastICAgenericsggplot2gluegraphgridExtragtableHSMMSingleCelligraphirlbaisobandlabelinglatticeleidenbaselifecyclelimmamagrittrMASSMatrixmatrixStatsmgcvmunsellnlmepheatmappillarpkgconfigplyrproxyR6RANNRBGLRColorBrewerRcppRcppEigenRCurlreshape2rlangRtsneRUnitscalesslamstatmodstringistringrtibbletidyselectutf8vctrsVGAMviridisviridisLitewithrXML

Monocle: Cell counting, differential expression, and trajectory analysis for single-cell RNA-Seq experiments

Rendered frommonocle-vignette.Rnwusingknitr::knitron Nov 18 2024.

Last update: 2017-10-23
Started: 2014-07-10

Readme and manuals

Help Manual

Help pageTopics
Add a new cell typeaddCellType
Branched expression analysis modeling (BEAM).BEAM
Test for branch-dependent expressionbranchTest
Build a CellDataSet that splits cells among two branchesbuildBranchCellDataSet
Compute the area between curves (ABC) for branch-dependent genescalABCs
Calibrate_per_cell_total_proposalcalibrate_per_cell_total_proposal
Calculate the Instantaneous Log Ratio between two branchescalILRs
The CellDataSet classCellDataSet CellDataSet-class
Methods for the CellDataSet classCellDataSet,ANY,ANY-method CellDataSet-methods estimateDispersions,CellDataSet-method estimateSizeFactors,CellDataSet-method sizeFactors,CellDataSet-method sizeFactors<-,CellDataSet,numeric-method
Get the matrix of pairwise distances between cellscellPairwiseDistances
Sets the matrix containing distances between each pair of cells used by Monocle during cell ordering. Not intended to be called directly.cellPairwiseDistances<-
The CellType classCellType CellType-class
The CellTypeHierarchy classCellTypeHierarchy CellTypeHierarchy-class
Cluster cells into a specified number of groups based on .clusterCells
Clusters genes by pseudotime trend.clusterGenes
Compare model fitscompareModels
Calculate divergence times for branch-dependent genesdetectBifurcationPoint
Detects genes above minimum threshold.detectGenes
Helper function for parallel differential expression testingdiff_test_helper
Test genes for differential expressiondifferentialGeneTest
Retrieve a table of values specifying the mean-variance relationshipdispersionTable
Find the most commonly occuring relative expression value in each cellestimate_t
Helper function to estimate dispersionsestimateDispersionsForCellDataSet
Function to calculate the size factor for the single-cell RNA-seq data @importFrom stats medianestimateSizeFactorsForMatrix
Export a monocle CellDataSet object to the Seurat single cell analysis toolkit.exportCDS
Extract a linear ordering of cells from a PQ treeextract_good_branched_ordering
Helper function for parallel VGAM fittingfit_model_helper
Fits a model for each gene in a CellDataSet object.fitModel
Fit smooth spline curves and return the residuals matrixgenSmoothCurveResiduals
Fit smooth spline curves and return the response matrixgenSmoothCurves
Return the names of classic muscle genesget_classic_muscle_markers
Import a Seurat object and convert it to a monocle cds.importCDS
Build a CellDataSet from the HSMMSingleCell packageload_HSMM
Return a CellDataSet of classic muscle genes.load_HSMM_markers
Build a CellDataSet from the data stored in inst/extdata directory.load_lung
Test genes for cell type-dependent expressionmarkerDiffTable
Multicore apply-like function for CellDataSetmcesApply
Retrieves the minimum spanning tree generated by Monocle during cell ordering.minSpanningTree
Set the minimum spanning tree generated by Monocle during cell ordering.minSpanningTree<-
Creates a new CellDateSet object.newCellDataSet
Classify cells according to a set of markerscalculateMarkerSpecificity classifyCells newCellTypeHierarchy
Return an ordering for a P node in the PQ treeorder_p_node
Orders cells according to pseudotime.orderCells
Plots clusters of cells .plot_cell_clusters
Plots the minimum spanning tree on cells.plot_cell_trajectory
Plots kinetic clusters of genes.plot_clusters
Not sure we're ready to release this one quite yet: Plot the branch genes in pseduotime with separate branch curvesplot_coexpression_matrix
Plots the minimum spanning tree on cells.plot_complex_cell_trajectory
Create a heatmap to demonstrate the bifurcation of gene expression along two branchs @description returns a heatmap that shows changes in both lineages at the same time. It also requires that you choose a branch point to inspect. Columns are points in pseudotime, rows are genes, and the beginning of pseudotime is in the middle of the heatmap. As you read from the middle of the heatmap to the right, you are following one lineage through pseudotime. As you read left, the other. The genes are clustered hierarchically, so you can visualize modules of genes that have similar lineage-dependent expression patterns.plot_genes_branched_heatmap
Plot the branch genes in pseduotime with separate branch curves.plot_genes_branched_pseudotime
Plots expression for one or more genes as a function of pseudotimeplot_genes_in_pseudotime
Plots expression for one or more genes as a jittered, grouped pointsplot_genes_jitter
Plots the number of cells expressing one or more genes as a barplotplot_genes_positive_cells
Plots expression for one or more genes as a violin plotplot_genes_violin
Create a heatmap to demonstrate the bifurcation of gene expression along multiple branchesplot_multiple_branches_heatmap
Create a kinetic curves to demonstrate the bifurcation of gene expression along multiple branchesplot_multiple_branches_pseudotime
Plots genes by mean vs. dispersion, highlighting those selected for orderingplot_ordering_genes
Plots the percentage of variance explained by the each component based on PCA from the normalized expression data using the same procedure used in reduceDimension function.plot_pc_variance_explained
Plots a pseudotime-ordered, row-centered heatmapplot_pseudotime_heatmap
Plots the decision map of density clusters .plot_rho_delta
Plots the minimum spanning tree on cells. This function is deprecated.plot_spanning_tree
Recursively builds and returns a PQ tree for the MSTpq_helper
Get the weights needed to lift cells back to high dimensional expression space.reducedDimA
Get the weights needed to lift cells back to high dimensional expression space.reducedDimA<-
Retrieves the the whitening matrix during independent component analysis.reducedDimK
Sets the the whitening matrix during independent component analysis.reducedDimK<-
Retrieves the coordinates of each cell in the reduced-dimensionality space generated by calls to reduceDimension.reducedDimS
Set embedding coordinates of each cell in a CellDataSet.reducedDimS<-
Get the whitened expression values for a CellDataSet.reducedDimW
Sets the whitened expression values for each cell prior to independent component analysis. Not intended to be called directly.reducedDimW<-
Compute a projection of a CellDataSet object into a lower dimensional spacereduceDimension
Transform relative expression values into absolute transcript counts.relative2abs
Response valuesresidualMatrix
Calculates response values.responseMatrix
Select the most cell type specific markersselectTopMarkers
Marks genes for clusteringsetOrderingFilter
Spike-in transcripts data.spike_df
Return a variance-stabilized matrix of expression valuesvstExprs