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
| Name | Required | Description | Default |
|---|---|---|---|
| aggregate_method | No | Method aggregation approach: 'mean' for mean rank, 'rra' for RobustRankAggregate. | rra |
| base | No | Exponent base used to reverse the log-transformation of the matrix. Relevant only for the `logfc` method. | |
| de_method | No | Differential expression method used to rank genes according to 1vsRest. | t-test |
| expr_prop | No | Minimum expression proportion for the ligands and receptors in the corresponding cell identities. Set to 0 to return unfiltered results. | |
| groupby | Yes | Key to be used for grouping or clustering cells (e.g., cell type annotations). | |
| key_added | No | Key under which the results will be stored in adata.uns. | liana_res |
| layer | No | Layer in AnnData.layers to use. If None, use AnnData.X. | |
| min_cells | No | Minimum cells per cell identity to be considered for downstream analysis. | |
| n_jobs | No | Number of jobs to run in parallel. | |
| n_perms | No | Number of permutations for permutation-based methods. If None, no permutation testing is performed. | |
| resource_name | No | Name of the resource to be used for ligand-receptor inference. See `li.rs.show_resources()` for available resources. | consensus |
| return_all_lrs | No | Whether to return all ligand-receptor pairs, or only those that surpass the expr_prop threshold. | |
| use_raw | No | Use 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"
}