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.
- min_cell_num
The minimal number of cells allowed in nodes.
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()
,
PlotDeltaEnrichmentPrunedTree()
,
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()