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dynwrap

Creating a trajectory
Adapting a trajectory model
Calculations from a trajectory
Creating a TI method
Running a TI method
Other

dynwrap 1.0.1 (unreleased)

MINOR CHANGE: Make create_ti_method_definition() actually work
DOCUMENTATION: Added examples for each trajectory wrapper
DOCUMENTATION: Added vignette discussing wrapper types
DOCUMENTATION: Added vignette discussing create_ti_method_definition()

dynwrap 1.0.0 (28-03-2019)

MAJOR CHANGE: Add support for Singularity 3.0, drop support for previous releases of Singularity and singularity-hub.
MAJOR CHANGE: dynwrap now always works with sparse count and expression matrices
FEATURE: Add create_ti_method_definition() to create a definition from a local script.
DOCUMENTATION: Major update of all documentation for dynbenchmark publication
MINOR CHANGE: Rename compute_tented_geodesic_distances() to calculate_geodesic_distances()
MINOR CHANGE: Harmonisation of function arguments to either dataset or trajectory

Creating a trajectory Methods to create a trajectory
`add_branch_trajectory`	Create 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_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_projection`	Constructs a trajectory by projecting cells within a dimensionality reduction onto a backbone formed by a milestone network. Optionally, a cell grouping can be given which will restrict the edges on which a cell can be projected.
`add_end_state_probabilities`	Multifurcating trajectory with end state probabilities
`add_linear_trajectory`	Constructs a linear trajectory using the pseudotime values of each cell.
`add_trajectory` `is_wrapper_with_trajectory`	Define a trajectory dataset given its milestone network and milestone percentages or progressions
`wrap_data` `is_data_wrapper`	A data wrapper for datasets and trajectories
Adapting a trajectory model Methods to adapt a trajectory
`add_cell_waypoints` `is_wrapper_with_waypoint_cells`	Add cell waypoints to a wrapped trajectory
`add_dimred` `is_wrapper_with_dimred` `get_dimred`	Add or create a dimensionality reduction
`add_expression` `is_wrapper_with_expression` `get_expression`	Add count and normalised expression values to a dataset
`add_grouping` `is_wrapper_with_grouping` `get_grouping`	Add a cell grouping to a dataset
`add_root` `add_root_using_expression` `is_rooted`	Root the trajectory
`add_tde_overall`	Add information on overall differentially expressed features
`add_timings` `is_wrapper_with_timings` `add_timing_checkpoint`	Add timings checkpoints
`add_waypoints` `is_wrapper_with_waypoints` `select_waypoints`	Add or create waypoints to a trajectory
`gather_cells_at_milestones`	"Gather" cells to their closest milestones
`label_milestones` `label_milestones_markers` `is_wrapper_with_milestone_labelling` `get_milestone_labelling`	Label milestones either manually (`label_milestones`) or using marker genes (`label_milestones_markers`)
`simplify_trajectory`	Simplify a trajectory by removing transient milestones
Calculations from a trajectory Deriving features from a trajectory model
`calculate_pseudotime` `add_pseudotime`	Add or calculate pseudotime as distance from the root
`calculate_average_by_group`	Calculate mean values per cell group
`calculate_average_by_milestone_percentages`	Calculate mean values by milestone percentages
`calculate_geodesic_distances` `compute_tented_geodesic_distances`	Calculate geodesic distances between cells in a trajectory
`calculate_trajectory_dimred`	Layout the trajectory and its cells in 2 dimensions
`group_from_trajectory` `group_onto_trajectory_edges` `group_onto_nearest_milestones`	Create a grouping from a trajectory
Creating a TI method Methods to create a TI method wrapper
`allowed_inputs`	All allowed inputs
`convert_definition`	Convert a definition loaded in from a yaml
`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 wrapper
`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_parameters`	Meta information on the parameters of the TI method
`def_wrapper`	Meta information on the wrapper
`definition` `is_ti_method`	Create a definition
`.method_process_definition`	Method process definition
`get_default_parameters`	Get the default parameters of a method
`prior_usages`	Metadata on prior usages
`priors`	Metadata on priors
`trajectory_type_dag`	A DAG of trajectory types
`trajectory_types`	Metadata on the trajectory types
`wrapper_types`	Metadata on wrapper types
Running a TI method Methods to run one or more TI methods
`add_prior_information` `is_wrapper_with_prior_information` `generate_prior_information`	Add prior information to a data wrapper
`get_ti_methods`	Return all TI ti_methods
`infer_trajectories` `infer_trajectory`	Infer trajectories
`wrap_expression`	Create a wrapper object with expression and counts
Other
`allowed_outputs`	All allowed outputs
`classify_milestone_network`	Classify a milestone network
`convert_milestone_percentages_to_progressions`	Convert milestone percentages to progressions
`convert_progressions_to_milestone_percentages`	Convert progressions to milestone percentages
`determine_cell_trajectory_positions`	Determine the positions of all cells in the trajectory
`dynwrap` `dynwrap-package`	This R package contains the code for a common model of single-cell trajectories.
`example_dataset`	Example dataset
`generate_parameter_documentation`	Generate the parameter documentation of a method, use with `@eval`
`get_divergence_triangles`	Helper function for processing divergence regions
`random_seed`	Generate a random seed
`select_waypoint_cells`	Select the waypoint cells
`simplify_igraph_network`	Simplify an igraph network such that consecutive linear edges are removed
`wrap_output_list`	Transform a list of data objects to a dynwrap trajectory

dynwrap

dynwrap 1.0.1 (unreleased)

dynwrap 1.0.0 (28-03-2019)

Creating a trajectory

Adapting a trajectory model

Calculations from a trajectory

Creating a TI method

Running a TI method

Other