Note that the given data wrapper requires a trajectory and expression values to have been added already.
For example, what are the start cells, the end cells, to which milestone does each cell belong to, ...
add_prior_information(dataset, start_id = NULL, end_id = NULL, groups_id = NULL, groups_network = NULL, features_id = NULL, groups_n = NULL, start_n = NULL, end_n = NULL, timecourse_continuous = NULL, timecourse_discrete = NULL, verbose = TRUE) is_wrapper_with_prior_information(dataset) generate_prior_information(cell_ids, milestone_ids, milestone_network, milestone_percentages, progressions, divergence_regions, expression, feature_info = NULL, cell_info = NULL, marker_fdr = 0.005, given = NULL, verbose = FALSE)
The start cells
The end cells
The grouping of cells, a dataframe with cell_id and group_id
The network between groups, a dataframe with from and to
The features (genes) important for the trajectory
Number of branches
Number of start states
Number of end states
The time for every cell
The time for every cell in groups
Whether or not to print informative messages
The ids of the cells.
The ids of the milestones in the trajectory. Type: Character vector.
The network of the milestones. Type: Data frame(from = character, to = character, length = numeric, directed = logical).
A data frame specifying what percentage milestone each cell consists of. Type: Data frame(cell_id = character, milestone_id = character, percentage = numeric).
Specifies the progression of a cell along a transition in the milestone_network. Type: Data frame(cell_id = character, from = character, to = character, percentage = numeric).
A data frame specifying the divergence regions between milestones (e.g. a bifurcation). Type: Data frame(divergence_id = character, milestone_id = character, is_start = logical).
The normalised expression values with genes in columns and cells in rows
Optional meta-information of the features, a data.frame with at least feature_id as column
Optional meta-information pertaining the cells.
Maximal FDR value for a gene to be considered a marker
Prior information already calculated
The dataset has to contain a trajectory for this to work