Representing and Inferring Single-Cell Trajectories


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Documentation for package ‘dynwrap’ version 1.2.2

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.method_process_definition Method process definition
add_attraction Add attraction of cells using RNA velocity
add_branch_trajectory Construct a trajectory given its branch network and the pseudotime of the cells on one of the branches.
add_cell_graph Constructs a trajectory using a graph between cells, by mapping cells onto a set of backbone cells.
add_cell_waypoints Add or select waypoint cells of a trajectory
add_cluster_graph Constructs a trajectory using a cell grouping and a network between groups. Will use an existing grouping if it is present in the dataset.
add_cyclic_trajectory Constructs a circular trajectory using the pseudotime values of each cell.
add_dimred Add or create a dimensionality reduction
add_dimred_projection Constructs a trajectory by projecting cells within a dimensionality reduction
add_end_state_probabilities Constructs a multifurcating trajectory using end state probabilities
add_expression Add count and normalised expression values to a dataset
add_feature_importance Add a feature importance to a dataset
add_grouping Add a cell grouping to a dataset
add_linear_trajectory Constructs a linear trajectory using pseudotime values
add_prior_information Add or compute prior information for a trajectory
add_pseudotime Add or calculate pseudotime as distance from the root
add_regulatory_network Add a GRN to a dynwrap object
add_root Root the trajectory
add_root_using_expression Root the trajectory
add_tde_overall Add information on overall differentially expressed features
add_timings Add timings to a trajectory
add_timing_checkpoint Add timings to a trajectory
add_trajectory Construct a trajectory given its milestone network and milestone percentages or progressions
add_waypoints Add or create waypoints to a trajectory
allowed_inputs All allowed inputs for a TI method
allowed_outputs All allowed outputs for a TI method
calculate_attraction Calculate the attraction of cells to other cells using velocity
calculate_average_by_group Calculate average values of a matrix
calculate_geodesic_distances Calculate geodesic distances between cells in a trajectory
calculate_pseudotime Add or calculate pseudotime as distance from the root
calculate_trajectory_dimred Layout the trajectory and its cells in 2 dimensions using a graph layout
classify_milestone_network Classify a milestone network
compute_tented_geodesic_distances Calculate geodesic distances between cells in a trajectory
convert_definition Convert a definition loaded in from a yaml
convert_milestone_percentages_to_progressions Conversion between milestone percentages and progressions
convert_progressions_to_milestone_percentages Conversion between milestone percentages and progressions
create_ti_method_container Create a TI method from a docker / singularity container
create_ti_method_definition Create a TI method from a local method definition file
create_ti_method_r Create a TI method from an R function wrapper
definition Create a definition
def_author Meta information on an author
def_container Meta information on the container in which the wrapper resides
def_manuscript Meta information on the manuscript
def_method Define meta information on the TI method.
def_package Meta information on the package in which the TI function resides
def_parameters Meta information on the parameters of the TI method
def_wrapper Meta information on the wrapper
determine_cell_trajectory_positions Add or select waypoint cells of a trajectory
dynwrap Inferring and adapting single-cell trajectories
example_dataset Example dataset
example_trajectory Example trajectory
flip_edges Flip a set of edges of the milestone network
gather_cells_at_milestones Gather cells to their closest milestones
generate_parameter_documentation Generate the parameter documentation of a method, use with @eval
generate_prior_information Add or compute prior information for a trajectory
get_default_parameters Get the default parameters of a method
get_dimred Add or create a dimensionality reduction
get_expression Add count and normalised expression values to a dataset
get_grouping Add a cell grouping to a dataset
get_milestone_labelling Label milestones either manually ('label_milestones') or using marker genes ('label_milestones_markers')
get_ti_methods Return all TI that are installed in one or more packages
group_from_trajectory Create a grouping from a trajectory
group_onto_nearest_milestones Create a grouping from a trajectory
group_onto_trajectory_edges Create a grouping from a trajectory
infer_trajectories Infer one or more trajectories from a single-cell dataset
infer_trajectory Infer one or more trajectories from a single-cell dataset
is_data_wrapper A data wrapper for datasets and trajectories
is_rooted Root the trajectory
is_ti_method Create a definition
is_wrapper_with_dimred Add or create a dimensionality reduction
is_wrapper_with_expression Add count and normalised expression values to a dataset
is_wrapper_with_feature_importance Add a feature importance to a dataset
is_wrapper_with_grouping Add a cell grouping to a dataset
is_wrapper_with_milestone_labelling Label milestones either manually ('label_milestones') or using marker genes ('label_milestones_markers')
is_wrapper_with_prior_information Add or compute prior information for a trajectory
is_wrapper_with_timings Add timings to a trajectory
is_wrapper_with_trajectory Construct a trajectory given its milestone network and milestone percentages or progressions
is_wrapper_with_waypoints Add or create waypoints to a trajectory
is_wrapper_with_waypoint_cells Add or select waypoint cells of a trajectory
label_milestones Label milestones either manually ('label_milestones') or using marker genes ('label_milestones_markers')
label_milestones_markers Label milestones either manually ('label_milestones') or using marker genes ('label_milestones_markers')
priors Metadata on priors
prior_usages Metadata on prior usages
project_milestones Project a trajectory onto a dimensionality reduction
project_trajectory Project a trajectory onto a dimensionality reduction
project_waypoints Project waypoints of a trajectory (e.g. milestones) into a space defined by cells (e.g. expression or a dimensionality reduction)
random_seed Generate a random seed
remove_root Root the trajectory
select_waypoints Add or create waypoints to a trajectory
select_waypoint_cells Add or select waypoint cells of a trajectory
simplify_igraph_network Simplify an igraph network such that consecutive linear edges are removed
simplify_trajectory Simplify a trajectory by removing transient milestones
trajectory_types Metadata on the trajectory types
trajectory_type_dag A DAG connecting different trajectory types
wrapper_types Metadata on wrapper types
wrap_data A data wrapper for datasets and trajectories
wrap_expression Create a wrapper object with expression and counts