Package: monocle3 1.3.7

Brent Ewing

monocle3: Clustering, Differential Expression, and Trajectory Analysis for Single-Cell RNA-Seq

Monocle 3 performs clustering, differential expression and trajectory 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 3 also performs differential expression analysis, clustering, visualization, and other useful tasks on single-cell expression data. It is designed to work with RNA-Seq data, but could be used with other types as well.

Authors:Hannah Pliner [aut], Xiaojie Qiu [aut], Cole Trapnell [aut], Brent Ewing [cre]

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NEWS

# Install 'monocle3' in R:
install.packages('monocle3', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/cole-trapnell-lab/monocle3/issues

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

On CRAN:

single-cell-rna-seq

67 exports 324 stars 6.40 score 184 dependencies 2 dependents 1.9k scripts

Last updated 5 months agofrom:98402ed0c1. Checks:OK: 1 ERROR: 8. Indexed: no.

TargetResultDate
Doc / VignettesOKAug 30 2024
R-4.5-win-x86_64ERRORAug 30 2024
R-4.5-linux-x86_64ERRORAug 30 2024
R-4.4-win-x86_64ERRORAug 30 2024
R-4.4-mac-x86_64ERRORAug 30 2024
R-4.4-mac-aarch64ERRORAug 30 2024
R-4.3-win-x86_64ERRORAug 30 2024
R-4.3-mac-x86_64ERRORAug 30 2024
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Exports:aggregate_gene_expressionalign_cdsalign_transformchoose_cellschoose_graph_segmentsclear_cds_slotscluster_cellsclusterscoefficient_tablecombine_cdscompare_modelsdetect_genesestimate_size_factorsevaluate_fitsexprsfDatafData<-find_gene_modulesfit_modelsfix_missing_cell_labelsgenerate_garnett_marker_fileget_citationsgraph_testidentity_tablelearn_graphload_a549load_cellranger_dataload_mm_dataload_monocle_objectsload_mtx_dataload_transform_modelsload_worm_embryoload_worm_l2make_cds_nn_indexmake_nn_indexmodel_predictionsnew_cell_data_setnormalized_countsorder_cellspartitionspDatapData<-plot_cellsplot_cells_3dplot_genes_by_groupplot_genes_in_pseudotimeplot_genes_violinplot_pc_variance_explainedplot_percent_cells_positivepreprocess_cdspreprocess_transformprincipal_graphprincipal_graph_auxprincipal_graph_aux<-principal_graph<-pseudotimereduce_dimensionreduce_dimension_transformsave_monocle_objectssave_transform_modelssearch_cds_nn_indexsearch_nn_indexsearch_nn_matrixset_cds_nn_indexsize_factorstop_markerstransfer_cell_labels

Dependencies:abindaskpassassertthatbase64encbatchelorbeachmatbeeswarmBHbiglmBiobaseBiocGenericsBiocNeighborsBiocParallelBiocSingularbootbslibcachemCairoclassclassIntclicodetoolscolorspacecommonmarkcpp11crayoncrosstalkcurldata.tableDBIDelayedArrayDelayedMatrixStatsdeldirdigestdplyrdqrnge1071evaluatefansifarverfastmapFNNfontawesomeformatRfsfurrrfutile.loggerfutile.optionsfuturegenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggbeeswarmggplot2ggrastrggrepelglobalsgluegridExtragrrgtableHDF5ArrayhighrhtmltoolshtmlwidgetshttpuvhttrigraphIRangesirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenbaselifecyclelimmalistenvlme4lmtestmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminqamunsellnlmenloptropensslparallellypbapplypbmcapplypheatmappillarpkgconfigplotlyplyrpngpromisesproxypsclpurrrR6raggRANNrappdirsRColorBrewerRcppRcppAnnoyRcppEigenRcppHNSWRcppProgressreshape2ResidualMatrixrhdf5rhdf5filtersRhdf5libRhpcBLASctlrlangrmarkdownrsampleRSpectrarsvdRtsnes2S4ArraysS4VectorssassScaledMatrixscalesscuttlesfshinySingleCellExperimentsitmoslamslidersnowsourcetoolsspSparseArraysparseMatrixStatsspDataspdepspeedglmstatmodstringistringrSummarizedExperimentsyssystemfontstextshapingtibbletidyrtidyselecttinytexUCSC.utilsunitsutf8uwotvctrsviporviridisviridisLitewarpwithrwkxfunxtableXVectoryamlzlibbioczoo

Monocle3: Cell counting, differential expression, and trajectory analysis for single-cell RNA-Seq experiments

Rendered frommonocle3-vignette.Rnwusingknitr::knitron Aug 30 2024.

Last update: 2022-05-23
Started: 2022-05-23

Readme and manuals

Help Manual

Help pageTopics
Creates a matrix with aggregated expression values for arbitrary groups of genesaggregate_gene_expression
Align cells from different groups within a cdsalign_cds
Apply an alignment transform model to a cell_data_set.align_transform
Function to automatically learn the structure of data by either using L1-graph or the spanning-tree formulizationcalc_principal_graph
The cell_data_set classcell_data_set cell_data_set-class
Methods for the cell_data_set classcell_data_set-methods
Choose cells interactively to subset a cdschoose_cells
Choose cells along the path of a principal graphchoose_graph_segments
Clear CDS slotsclear_cds_slots
Cluster cells using Louvain/Leiden community detectioncluster_cells
Generic to extract clusters from CDS objectclusters
Method to extract clusters from CDS objectclusters,cell_data_set-method
Extract coefficient table from a fit_models result.coefficient_table
Combine a list of cell_data_set objectscombine_cds
Compare goodness of fit of two models.compare_models
Detects genes above minimum threshold.detect_genes
Function to calculate size factors for single-cell RNA-seq dataestimate_size_factors
Evaluate fit of model objects.evaluate_fits
Generic to access cds count matrixexprs
Method to access cds count matrixexprs,cell_data_set-method
Generic to access cds rowData tablefData
Method to access cds rowData tablefData,cell_data_set-method
Generic to set cds rowData tablefData<-
Method to set cds rowData tablefData<-,cell_data_set-method
Cluster genes into modules that are co-expressed across cells.find_gene_modules
Fits a model for each gene in a cell_data_set object.fit_models
Replace NA cell column data values left after running transfer_cell_labels.fix_missing_cell_labels
Function to reproduce the behavior of eye function in matlabgenerate_centers
Generate a Garnett marker file from top_markers output.generate_garnett_marker_file
Access citations for methods used during analysis.get_citations
Get a genome from Cell Ranger outputget_genome_in_matrix_path
Test genes for differential expression based on the low dimensional embedding and the principal graphgraph_test
Report matrix and model identity information.identity_table
Learn principal graph from the reduced dimension space using reversed graph embeddinglearn_graph
Build a small cell_data_set.load_a549
Load data from the 10x Genomics Cell Ranger pipelineload_cellranger_data
Load data from matrix market format files.load_mm_data
Load a full Monocle3 cell_data_set.load_monocle_objects
Load data from matrix market formatload_mtx_data
Load transform models into a cell_data_set.load_transform_models
Build a cell_data_set from C. elegans embryo data.load_worm_embryo
Build a cell_data_set from C. elegans L2 data.load_worm_l2
Make and store a nearest neighbor index in the cell_data_set.make_cds_nn_index
Make a nearest neighbor index.make_nn_index
Multicore apply-like function for cell_data_setmc_es_apply
Predict values of new data using fit_models model.model_predictions
Create a new cell_data_set object.new_cell_data_set
Return a size-factor normalized and (optionally) log-transformed expression matrixnormalized_counts
Orders cells according to pseudotime.order_cells
Generic to extract partitions from CDS objectpartitions
Method to extract partitions from CDS objectpartitions,cell_data_set-method
Generic to access cds colData tablepData
Method to access cds colData tablepData,cell_data_set-method
Generic to set cds colData tablepData<-
Method to set cds colData tablepData<-,cell_data_set-method
Plots the cells along with their trajectories.plot_cells
Plot a dataset and trajectory in 3 dimensionsplot_cells_3d
Create a dot plot to visualize the mean gene expression and percentage of expressed cells in each group of cellsplot_genes_by_group
Plots expression for one or more genes as a function of pseudotimeplot_genes_in_pseudotime
Plot expression for one or more genes as a violin plotplot_genes_violin
Plots the fraction of variance explained by the each component based on PCA from the normalized expression data determined using preprocess_cds. This is the fraction of the component variance relative to the variance of the components retained in the PCA; not the total variance.plot_pc_variance_explained
Plots the number of cells expressing one or more genes above a given value as a barplotplot_percent_cells_positive
Preprocess a cds to prepare for trajectory inferencepreprocess_cds
Apply a preprocess transform model to a cell_data_set.preprocess_transform
Generic to extract principal graph from CDSprincipal_graph
Generic to extract principal graph auxiliary information from CDSprincipal_graph_aux
Method to extract principal graph auxiliary information from CDSprincipal_graph_aux,cell_data_set-method
Generic to set principal graph auxiliary information into CDSprincipal_graph_aux<-
Method to set principal graph auxiliary information into CDSprincipal_graph_aux<-,cell_data_set-method
Method to extract principal graph from CDSprincipal_graph,cell_data_set-method
Generic to set principal graph to CDSprincipal_graph<-
Generic to set principal graph to CDSprincipal_graph<-,cell_data_set-method
Generic to extract pseudotime from CDS objectpseudotime
Method to extract pseudotime from CDS objectpseudotime,cell_data_set-method
Compute a projection of a cell_data_set object into a lower dimensional space with non-linear dimension reduction methodsreduce_dimension
Apply a reduce_dimension transform model to a cell_data_set.reduce_dimension_transform
function to reproduce the behavior of repmat function in matlab to replicate and tile an matrixrepmat
Save a Monocle3 full cell_data_set.save_monocle_objects
Save cell_data_set transform models.save_transform_models
Search a nearest neighbor index that is stored in the cds.search_cds_nn_index
Search a nearest neighbor index.search_nn_index
Search a subject matrix for nearest neighbors to a query_matrix.search_nn_matrix
Set a nearest neighor index in the cell_data_set.set_cds_nn_index
Verify and set nearest neighbor parameter list.set_nn_control
Get the size factors from a cds object.size_factors
Set the size factor values in the cell_data_setsize_factors<-
Function to calculate the third term in the objective functionsoft_assignment
Principal Components Analysissparse_prcomp_irlba
Identify the genes most specifically expressed in groups of cellstop_markers
Transfer cell column data from a reference to a query cell_data_set.transfer_cell_labels