This function processes gating decisions based on given markers and their states, managing data from a root node to determine optimal gating paths based on entropy and enrichment calculations. It handles decision-making at each node of a gating tree, determining whether to continue subdividing or to terminate based on statistical thresholds and data availability.
Usage
general_node_rule(
currentNode,
root_data,
sampledef,
neg_gate,
expr_group,
ctrl_group,
total_cell_per_file,
usedmarkers,
min_cell_num = 25
)Arguments
- currentNode
A list representing the current node in the gating tree, including markers used, current node indices, and gating history.
- root_data
A data frame containing the complete dataset for analysis.
- sampledef
A data frame specifying sample definitions and group assignments.
- neg_gate
A list containing thresholds for negative gating decisions.
- expr_group
The name of the experimental group within `sampledef`.
- ctrl_group
The name of the control group within `sampledef`.
- total_cell_per_file
A data frame mapping file names to total cell counts per file.
- usedmarkers
A vector of markers that have already been used in previous steps of gating.
- available_markers
A character vector of markers that are still available for gating.
Value
A list structure describing the outcomes at the current node, including any child nodes created, or indicators if the node processing leads to termination.
See also
Other GatingTree:
GatingTreeToDF(),
PlotDeltaEnrichment(),
PruneGatingTree(),
addChildNode(),
add_prune(),
apply_gating_conditions(),
baseline_entropy(),
calculate_enrichment(),
calculate_entropy(),
collect_all_enrichment(),
collect_all_entropy(),
collect_history(),
collect_leaf_enrichment(),
collect_markers(),
convertToDataTree(),
convert_to_diagrammer(),
count_nodes(),
createChildNode(),
createGatingTreeObject(),
findNodeByPath(),
find_and_update_nodes(),
gating_entropy(),
generate_marker_names(),
getNode(),
prune_tree(),
recursiveAddChildNode()