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ccc_rank_aggregate

Aggregate ligand-receptor interaction scores from multiple cell-cell communication methods to identify significant interactions using grouping, filtering, and ranking techniques, facilitating precise analysis of single-cell RNA sequencing data.

Instructions

Get an aggregate of ligand-receptor scores from multiple Cell-cell communication methods.

Input Schema

NameRequiredDescriptionDefault
aggregate_methodNoMethod aggregation approach: 'mean' for mean rank, 'rra' for RobustRankAggregate.rra
baseNoExponent base used to reverse the log-transformation of the matrix. Relevant only for the `logfc` method.
de_methodNoDifferential expression method used to rank genes according to 1vsRest.t-test
expr_propNoMinimum expression proportion for the ligands and receptors in the corresponding cell identities. Set to 0 to return unfiltered results.
groupbyYesKey to be used for grouping or clustering cells (e.g., cell type annotations).
key_addedNoKey under which the results will be stored in adata.uns.liana_res
layerNoLayer in AnnData.layers to use. If None, use AnnData.X.
min_cellsNoMinimum cells per cell identity to be considered for downstream analysis.
n_jobsNoNumber of jobs to run in parallel.
n_permsNoNumber of permutations for permutation-based methods. If None, no permutation testing is performed.
resource_nameNoName of the resource to be used for ligand-receptor inference. See `li.rs.show_resources()` for available resources.consensus
return_all_lrsNoWhether to return all ligand-receptor pairs, or only those that surpass the expr_prop threshold.
use_rawNoUse raw attribute of adata if present.

Input Schema (JSON Schema)

{ "description": "Input schema for LIANA's rank_aggregate method for cell-cell communication analysis.", "properties": { "aggregate_method": { "default": "rra", "description": "Method aggregation approach: 'mean' for mean rank, 'rra' for RobustRankAggregate.", "enum": [ "rra", "mean" ], "title": "Aggregate Method", "type": "string" }, "base": { "default": 2.718281828459045, "description": "Exponent base used to reverse the log-transformation of the matrix. Relevant only for the `logfc` method.", "title": "Base", "type": "number" }, "de_method": { "default": "t-test", "description": "Differential expression method used to rank genes according to 1vsRest.", "title": "De Method", "type": "string" }, "expr_prop": { "default": 0.1, "description": "Minimum expression proportion for the ligands and receptors in the corresponding cell identities. Set to 0 to return unfiltered results.", "title": "Expr Prop", "type": "number" }, "groupby": { "description": "Key to be used for grouping or clustering cells (e.g., cell type annotations).", "title": "Groupby", "type": "string" }, "key_added": { "default": "liana_res", "description": "Key under which the results will be stored in adata.uns.", "title": "Key Added", "type": "string" }, "layer": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Layer in AnnData.layers to use. If None, use AnnData.X.", "title": "Layer" }, "min_cells": { "default": 5, "description": "Minimum cells per cell identity to be considered for downstream analysis.", "title": "Min Cells", "type": "integer" }, "n_jobs": { "default": 1, "description": "Number of jobs to run in parallel.", "title": "N Jobs", "type": "integer" }, "n_perms": { "default": 1000, "description": "Number of permutations for permutation-based methods. If None, no permutation testing is performed.", "title": "N Perms", "type": "integer" }, "resource_name": { "default": "consensus", "description": "Name of the resource to be used for ligand-receptor inference. See `li.rs.show_resources()` for available resources.", "title": "Resource Name", "type": "string" }, "return_all_lrs": { "default": false, "description": "Whether to return all ligand-receptor pairs, or only those that surpass the expr_prop threshold.", "title": "Return All Lrs", "type": "boolean" }, "use_raw": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": true, "description": "Use raw attribute of adata if present.", "title": "Use Raw" } }, "required": [ "groupby" ], "title": "RankAggregateModel", "type": "object" }

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