from pydantic import (
Field,
ValidationInfo,
computed_field,
field_validator,
model_validator,BaseModel
)
from typing import Optional, List, Dict, Union, Literal, Tuple
class ListCCCMethodParam(BaseModel):
"""ListCCCMethodParam"""
pass
class RankAggregateParam(BaseModel):
"""Input schema for LIANA's rank_aggregate method for cell-cell communication analysis."""
groupby: str = Field(
..., # Required field
description="Key to be used for grouping or clustering cells (e.g., cell type annotations)."
)
resource_name: str = Field(
default="consensus",
description="Name of the resource to be used for ligand-receptor inference. See `li.rs.show_resources()` for available resources."
)
expr_prop: float = Field(
default=0.1,
description="Minimum expression proportion for the ligands and receptors in the corresponding cell identities. Set to 0 to return unfiltered results."
)
min_cells: int = Field(
default=5,
description="Minimum cells per cell identity to be considered for downstream analysis."
)
base: float = Field(
default=2.718281828459045, # e
description="Exponent base used to reverse the log-transformation of the matrix. Relevant only for the `logfc` method."
)
aggregate_method: Literal["rra", "mean"] = Field(
default="rra",
description="Method aggregation approach: 'mean' for mean rank, 'rra' for RobustRankAggregate."
)
return_all_lrs: bool = Field(
default=False,
description="Whether to return all ligand-receptor pairs, or only those that surpass the expr_prop threshold."
)
key_added: str = Field(
default="liana_res",
description="Key under which the results will be stored in adata.uns."
)
use_raw: Optional[bool] = Field(
default=True,
description="Use raw attribute of adata if present."
)
layer: Optional[str] = Field(
default=None,
description="Layer in AnnData.layers to use. If None, use AnnData.X."
)
de_method: str = Field(
default="t-test",
description="Differential expression method used to rank genes according to 1vsRest."
)
n_perms: int = Field(
default=1000,
description="Number of permutations for permutation-based methods. If None, no permutation testing is performed."
)
n_jobs: int = Field(
default=1,
description="Number of jobs to run in parallel."
)
class CCCParam(BaseModel):
"""Input schema for LIANA's cell-cell communication analysis."""
method: Literal[
"singlecellsignalr",
"connectome",
"cellphonedb",
"natmi",
"logfc",
"cellchat",
"geometric_mean",
"scseqcomm"
] = Field(
default="cellphonedb",
description="cell-cell communication method"
)
groupby: str = Field(
..., # Required field
description="Key to be used for grouping cells (e.g., cell type annotations)."
)
resource_name: str = Field(
default="consensus",
description="Name of the resource to be used for ligand-receptor inference. See `li.rs.show_resources()` for available resources."
)
expr_prop: float = Field(
default=0.1,
description="Minimum expression proportion for the ligands and receptors in the corresponding cell identities. Set to 0 to return unfiltered results."
)
min_cells: int = Field(
default=5,
description="Minimum cells per cell identity to be considered for downstream analysis."
)
base: float = Field(
default=2.718281828459045, # e
description="Exponent base used to reverse the log-transformation of the matrix. Relevant only for the `logfc` method."
)
return_all_lrs: bool = Field(
default=False,
description="Whether to return all ligand-receptor pairs, or only those that surpass the expr_prop threshold."
)
key_added: str = Field(
default="liana_res",
description="Key under which the results will be stored in adata.uns."
)
use_raw: Optional[bool] = Field(
default=True,
description="Use raw attribute of adata if present."
)
layer: Optional[str] = Field(
default=None,
description="Layer in AnnData.layers to use. If None, use AnnData.X."
)
de_method: str = Field(
default="t-test",
description="Differential expression method used to rank genes according to 1vsRest."
)
n_perms: int = Field(
default=1000,
description="Number of permutations for the permutation test. Relevant for CellPhoneDB method."
)
seed: int = Field(
default=1337,
description="Random seed for reproducibility."
)
n_jobs: int = Field(
default=1,
description="Number of jobs to run in parallel."
)
inplace: bool = Field(
default=True,
description="Whether to store results in place, or return them."
)
supp_columns: Optional[List[str]] = Field(
default=None,
description="Additional columns to be added from methods in liana, or columns from scanpy.tl.rank_genes_groups."
)
