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'))

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

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

software singlecell rnaseq atacseq normalization preprocessing dimensionreduction visualization qualitycontrol clustering classification annotation geneexpression differentialexpression single-cell-rna-seq

9.21 score 333 stars 1 packages 2.2k scripts 67 exports 185 dependencies

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

Target	Result	Date
Doc / Vignettes	OK	Oct 29 2024
R-4.5-win-x86_64	ERROR	Oct 29 2024
R-4.5-linux-x86_64	ERROR	Oct 29 2024
R-4.4-win-x86_64	ERROR	Oct 29 2024
R-4.4-mac-x86_64	ERROR	Oct 29 2024
R-4.4-mac-aarch64	ERROR	Oct 29 2024
R-4.3-win-x86_64	ERROR	Oct 29 2024
R-4.3-mac-x86_64	ERROR	Oct 29 2024
R-4.3-mac-aarch64	ERROR	Oct 29 2024

Exports:aggregate_gene_expression align_cds align_transform choose_cells choose_graph_segments clear_cds_slots cluster_cells clusters coefficient_table combine_cds compare_models detect_genes estimate_size_factors evaluate_fits exprs fData fData<-find_gene_modules fit_models fix_missing_cell_labels generate_garnett_marker_file get_citations graph_test identity_table learn_graph load_a549 load_cellranger_data load_mm_data load_monocle_objects load_mtx_data load_transform_models load_worm_embryo load_worm_l2 make_cds_nn_index make_nn_index model_predictions new_cell_data_set normalized_counts order_cells partitions pData pData<-plot_cells plot_cells_3d plot_genes_by_group plot_genes_in_pseudotime plot_genes_violin plot_pc_variance_explained plot_percent_cells_positive preprocess_cds preprocess_transform principal_graph principal_graph_aux principal_graph_aux<-principal_graph<-pseudotime reduce_dimension reduce_dimension_transform save_monocle_objects save_transform_models search_cds_nn_index search_nn_index search_nn_matrix set_cds_nn_index size_factors top_markers transfer_cell_labels

Dependencies:abind askpass assertthat assorthead base64enc batchelor beachmat beeswarm BH biglm Biobase BiocGenerics BiocNeighbors BiocParallel BiocSingular boot bslib cachem Cairo class classInt cli codetools colorspace commonmark cpp11 crayon crosstalk curl data.table DBI DelayedArray DelayedMatrixStats deldir digest dplyr dqrng e1071 evaluate fansi farver fastmap FNN fontawesome formatR fs furrr futile.logger futile.options future generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggbeeswarm ggplot2 ggrastr ggrepel globals glue gridExtra grr gtable HDF5Array highr htmltools htmlwidgets httpuv httr igraph IRanges irlba isoband jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval leidenbase lifecycle limma listenv lme4 lmtest magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime minqa munsell nlme nloptr openssl parallelly pbapply pbmcapply pheatmap pillar pkgconfig plotly plyr png promises proxy pscl purrr R6 ragg RANN rappdirs RColorBrewer Rcpp RcppAnnoy RcppEigen RcppHNSW RcppProgress reshape2 ResidualMatrix rhdf5 rhdf5filters Rhdf5lib RhpcBLASctl rlang rmarkdown rsample RSpectra rsvd Rtsne s2 S4Arrays S4Vectors sass ScaledMatrix scales scuttle sf shiny SingleCellExperiment sitmo slam slider snow sourcetools sp SparseArray sparseMatrixStats spData spdep speedglm statmod stringi stringr SummarizedExperiment sys systemfonts textshaping tibble tidyr tidyselect tinytex UCSC.utils units utf8 uwot vctrs vipor viridis viridisLite warp withr wk xfun xtable XVector yaml zlibbioc zoo

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

Rendered frommonocle3-vignette.Rnwusingknitr::knitron Oct 29 2024.

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

Help page	Topics
Creates a matrix with aggregated expression values for arbitrary groups of genes	aggregate_gene_expression
Align cells from different groups within a cds	align_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 formulization	calc_principal_graph
The cell_data_set class	cell_data_set cell_data_set-class
Methods for the cell_data_set class	cell_data_set-methods
Choose cells interactively to subset a cds	choose_cells
Choose cells along the path of a principal graph	choose_graph_segments
Clear CDS slots	clear_cds_slots
Cluster cells using Louvain/Leiden community detection	cluster_cells
Generic to extract clusters from CDS object	clusters
Method to extract clusters from CDS object	clusters,cell_data_set-method
Extract coefficient table from a fit_models result.	coefficient_table
Combine a list of cell_data_set objects	combine_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 data	estimate_size_factors
Evaluate fit of model objects.	evaluate_fits
Generic to access cds count matrix	exprs
Method to access cds count matrix	exprs,cell_data_set-method
Generic to access cds rowData table	fData
Method to access cds rowData table	fData,cell_data_set-method
Generic to set cds rowData table	fData<-
Method to set cds rowData table	fData<-,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 matlab	generate_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 output	get_genome_in_matrix_path
Test genes for differential expression based on the low dimensional embedding and the principal graph	graph_test
Report matrix and model identity information.	identity_table
Learn principal graph from the reduced dimension space using reversed graph embedding	learn_graph
Build a small cell_data_set.	load_a549
Load data from the 10x Genomics Cell Ranger pipeline	load_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 format	load_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_set	mc_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 matrix	normalized_counts
Orders cells according to pseudotime.	order_cells
Generic to extract partitions from CDS object	partitions
Method to extract partitions from CDS object	partitions,cell_data_set-method
Generic to access cds colData table	pData
Method to access cds colData table	pData,cell_data_set-method
Generic to set cds colData table	pData<-
Method to set cds colData table	pData<-,cell_data_set-method
Plots the cells along with their trajectories.	plot_cells
Plot a dataset and trajectory in 3 dimensions	plot_cells_3d
Create a dot plot to visualize the mean gene expression and percentage of expressed cells in each group of cells	plot_genes_by_group
Plots expression for one or more genes as a function of pseudotime	plot_genes_in_pseudotime
Plot expression for one or more genes as a violin plot	plot_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 barplot	plot_percent_cells_positive
Preprocess a cds to prepare for trajectory inference	preprocess_cds
Apply a preprocess transform model to a cell_data_set.	preprocess_transform
Generic to extract principal graph from CDS	principal_graph
Generic to extract principal graph auxiliary information from CDS	principal_graph_aux
Method to extract principal graph auxiliary information from CDS	principal_graph_aux,cell_data_set-method
Generic to set principal graph auxiliary information into CDS	principal_graph_aux<-
Method to set principal graph auxiliary information into CDS	principal_graph_aux<-,cell_data_set-method
Method to extract principal graph from CDS	principal_graph,cell_data_set-method
Generic to set principal graph to CDS	principal_graph<-
Generic to set principal graph to CDS	principal_graph<-,cell_data_set-method
Generic to extract pseudotime from CDS object	pseudotime
Method to extract pseudotime from CDS object	pseudotime,cell_data_set-method
Compute a projection of a cell_data_set object into a lower dimensional space with non-linear dimension reduction methods	reduce_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 matrix	repmat
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_set	size_factors<-
Function to calculate the third term in the objective function	soft_assignment
Principal Components Analysis	sparse_prcomp_irlba
Identify the genes most specifically expressed in groups of cells	top_markers
Transfer cell column data from a reference to a query cell_data_set.	transfer_cell_labels

Package: monocle3 1.3.7

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

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

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