calculate_qc_metrics

Calculate quality control metrics for single-cell RNA sequencing data, including total counts, gene numbers, and mitochondrial/ribosomal percentages to assess data quality.

Instructions

Calculate quality control metrics(common metrics: total counts, gene number, percentage of counts in ribosomal and mitochondrial) for AnnData.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`expr_type`	No	Name of kind of values in X.	counts
`var_type`	No	The kind of thing the variables are.	genes
`qc_vars`	No	Keys for boolean columns of .var which identify variables you could want to control for mark_var tool should be called frist when you want to calculate mt, ribo, hb, and check tool output for var columns
`percent_top`	No	List of ranks (where genes are ranked by expression) at which the cumulative proportion of expression will be reported as a percentage.
`layer`	No	If provided, use adata.layers[layer] for expression values instead of adata.X
`use_raw`	No	If True, use adata.raw.X for expression values instead of adata.X
`log1p`	No	Set to False to skip computing log1p transformed annotations.

Implementation Reference

src/scmcp/tool/pp.py:120-137 (handler)

Handler function that executes the calculate_qc_metrics tool logic by calling the mapped scanpy.pp.calculate_qc_metrics function on the active AnnData object with provided arguments and inplace=True.

def run_pp_func(ads, func, arguments):
    adata = ads.adata_dic[ads.active]
    if func not in pp_func:
        raise ValueError(f"不支持的函数: {func}")
    
    run_func = pp_func[func]
    parameters = inspect.signature(run_func).parameters
    arguments["inplace"] = True
    kwargs = {k: arguments.get(k) for k in parameters if k in arguments}
    try:
        res = run_func(adata, **kwargs)
        add_op_log(adata, run_func, kwargs)
    except KeyError as e:
        raise KeyError(f"Can not foud {e} column in adata.obs or adata.var")
    except Exception as e:
       raise e
    return res

src/scmcp/schema/pp.py:76-124 (schema)

Pydantic input schema model for the calculate_qc_metrics tool, including fields like qc_vars, percent_top, layer, use_raw, log1p with validation.

class CalculateQCMetrics(JSONParsingModel):
    """Input schema for the calculate_qc_metrics preprocessing tool."""
    
    expr_type: str = Field(
        default="counts",
        description="Name of kind of values in X."
    )
    
    var_type: str = Field(
        default="genes",
        description="The kind of thing the variables are."
    )
    
    qc_vars: Optional[Union[List[str], str]]  = Field(
        default=[],
        description=(
            "Keys for boolean columns of .var which identify variables you could want to control for "
            "mark_var tool should be called frist when you want to calculate mt, ribo, hb, and check tool output for var columns"
        )
    )
    
    percent_top: Optional[List[int]] = Field(
        default=[50, 100, 200, 500],
        description="List of ranks (where genes are ranked by expression) at which the cumulative proportion of expression will be reported as a percentage."
    )
    
    layer: Optional[str] = Field(
        default=None,
        description="If provided, use adata.layers[layer] for expression values instead of adata.X"
    )
    
    use_raw: bool = Field(
        default=False,
        description="If True, use adata.raw.X for expression values instead of adata.X"
    )
    log1p: bool = Field(
        default=True,
        description="Set to False to skip computing log1p transformed annotations."
    )
    
    @field_validator('percent_top')
    def validate_percent_top(cls, v: Optional[List[int]]) -> Optional[List[int]]:
        """验证 percent_top 中的值为正整数"""
        if v is not None:
            for rank in v:
                if not isinstance(rank, int) or rank <= 0:
                    raise ValueError("percent_top 中的所有值必须是正整数")
        return v

src/scmcp/tool/pp.py:27-31 (registration)

MCP Tool object registration defining the name, description, and input schema for calculate_qc_metrics.

calculate_qc_metrics = types.Tool(
    name="calculate_qc_metrics",
    description="Calculate quality control metrics(common metrics: total counts, gene number, percentage of counts in ribosomal and mitochondrial) for AnnData.",
    inputSchema=CalculateQCMetrics.model_json_schema(),
)

src/scmcp/tool/pp.py:91-91 (helper)
pp_func dictionary entry mapping the tool name to the wrapped scanpy function partial(sc.pp.calculate_qc_metrics, inplace=True).
```
"calculate_qc_metrics": partial(sc.pp.calculate_qc_metrics, inplace=True),
```

src/scmcp/tool/pp.py:104-117 (registration)

pp_tools dictionary that includes the calculate_qc_metrics tool, used by server.list_tools() to expose the tool.

pp_tools = {
    "filter_genes": filter_genes,
    "filter_cells": filter_cells,
    "calculate_qc_metrics": calculate_qc_metrics,
    "log1p": log1p,
    "normalize_total": normalize_total,
    "pca": pca,
    "highly_variable_genes": highly_variable_genes,
    "regress_out": regress_out,
    "scale": scale,
    "combat": combat,
    "scrublet": scrublet,
    "neighbors": neighbors,
}

SCMCP