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MONOCLE 3

Monocle 3 is an analysis toolkit for single-cell RNA-Seq experiments. To use this package, you will need the R statistical computing environment (version 3.0 or later) and several packages available through Bioconductor and CRAN.

Details on how to install and use Monocle 3 are available on our website:

http://cole-trapnell-lab.github.io/monocle3/

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Version

Version

0.1.3

License

MIT + file LICENSE

Maintainer

Cole Trapnell

Last Published

September 8th, 2021

Functions in monocle3 (0.1.3)

Evaluate the fits of model objects.

clusters,cell_data_set-method

Method to extract clusters from CDS object

exprs,cell_data_set-method

Method to access cds count matrix

calc_principal_graph

Function to automatically learn the structure of data by either using L1-graph or the spanning-tree formulization

Compares goodness of fit for two ways of fitting a set of genes' expression

find_gene_modules

Cluster genes into modules that are co-expressed across cells.

Generic to access cds rowData table

Combine a list of cell_data_set objects

Cluster cells based on Louvain community detection algorithm.

fit_model_helper

Helper function for model fitting

Multicore apply-like function for cell_data_set

Orders cells according to pseudotime.

find_nearest_vertex

Finds the nearest principal graph node

coefficient_table

Extracts a table of coefficients from a tibble containing model objects

my.aggregate.Matrix

A function to aggregate columns within a matrix.

Function to calculate the neighbors list with spatial weights for the chosen coding scheme from a cell dataset object

model_predictions

Predict output of fitted models and return as a matrix

Generic to extract clusters from CDS object

plot_pc_variance_explained

Plots the percentage of variance explained by the each component based on PCA from the normalized expression data determined using preprocess_cds.

clear_cds_slots

Clear CDS slots

choose_graph_segments

Choose cells interactively along the path of a principal graph

pData,cell_data_set-method

Method to access cds colData table

cell_data_set-methods

Methods for the cell_data_set class

Plot a dataset and trajectory in 3 dimensions

plot_genes_by_group

Create a dot plot to visualize the mean gene expression and percentage of expressed cells in each group of cells

Set the size factor values in the cell_data_set

function to reproduce the behavior of repmat function in matlab to replicate and tile an matrix

fData<-,cell_data_set-method

Method to set cds rowData table

estimate_size_factors

Function to calculate size factors for single-cell RNA-seq data

Detects genes above minimum threshold.

generate_garnett_marker_file

Generate a Garnett marker file from top_markers output.

new_cell_data_set

Create a new cell_data_set object.

Generic to set cds rowData table

plot_percent_cells_positive

Plots the number of cells expressing one or more genes above a given value as a barplot

Fits a model for each gene in a cell_data_set object.

generate_centers

Function to reproduce the behavior of eye function in matlab

fData,cell_data_set-method

Generic to access cds rowData table

Generic to access cds count matrix

normalized_counts

Return a size-factor normalized and (optionally) log-transformed expression matrix

Build a cell_data_set from the data stored in inst/extdata directory.

load_cellranger_data

Load data from the 10x Genomics Cell Ranger pipeline

Generic to extract partitions from CDS object

Load data from matrix market format

get_genome_in_matrix_path

Get a genome from Cell Ranger output

load_worm_embryo

Build a cell_data_set from the data stored in inst/extdata directory.

principal_graph_aux

Generic to extract principal graph auxiliary information from CDS

Generic to access cds colData table

pseudotime,cell_data_set-method

Method to extract pseudotime from CDS object

principal_graph<-,cell_data_set-method

Generic to set principal graph to CDS

Identify the genes most specifically expressed in groups of cells

principal_graph<-

Generic to set principal graph to CDS

principal_graph_aux,cell_data_set-method

Method to extract principal graph auxiliary information from CDS

principal_graph

Generic to extract principal graph from CDS

sparse_prcomp_irlba

Principal Components Analysis

partitions,cell_data_set-method

Method to extract partitions from CDS object

plot_genes_violin

Plot expression for one or more genes as a violin plot

Generic to extract pseudotime from CDS object

plot_genes_in_pseudotime

Plots expression for one or more genes as a function of pseudotime

Plots the cells along with their trajectories.

reduce_dimension

Compute a projection of a cell_data_set object into a lower dimensional space with non-linear dimension reduction methods

principal_graph_aux<-,cell_data_set-method

Method to set principal graph auxiliary information into CDS

principal_graph_aux<-

Generic to set principal graph auxiliary information into CDS

Generic to set cds colData table

Test genes for differential expression based on the low dimensional embedding and the principal graph

principal_graph,cell_data_set-method

Method to extract principal graph from CDS

Get the size factors from a cds object.

Learn principal graph from the reduced dimension space using reversed graph embedding

Preprocess a cds to prepare for trajectory inference

pData<-,cell_data_set-method

Method to set cds colData table

soft_assignment

Function to calculate the third term in the objective function

Cluster cells using Louvain community detection

The cell_data_set class

aggregate_gene_expression

Creates a matrix with aggregated expression values for arbitrary groups of genes

Choose cells interactively to subset a cds