Configuration Classes

DiffBio uses dataclasses for operator and pipeline configuration. All configurations inherit from Datarax's OperatorConfig base class.

Operator Configurations

Configuration classes for each operator are documented alongside their respective operators:

Operator	Config	Documentation
Smith-Waterman	SmithWatermanConfig	API Reference
Quality Filter	QualityFilterConfig	API Reference
Pileup	PileupConfig	API Reference
CNN Variant Classifier	CNNVariantClassifierConfig	API Reference
CNV Segmentation	CNVSegmentationConfig	API Reference
Soft K-Means	SoftClusteringConfig	API Reference
Harmony	BatchCorrectionConfig	API Reference
RNA Velocity	VelocityConfig	API Reference

Pipeline Configurations

Pipeline	Config	Documentation
Variant Calling	VariantCallingPipelineConfig	API Reference
Preprocessing	PreprocessingPipelineConfig	API Reference
Differential Expression	DEPipelineConfig	API Reference

Training Configuration

The training configuration is documented in the training utilities:

Config	Documentation
TrainingConfig	API Reference

Configuration Patterns

Base Configuration

All operator configs inherit from OperatorConfig:

from dataclasses import dataclass
from datarax.core.config import OperatorConfig

@dataclass(frozen=True)
class MyOperatorConfig(OperatorConfig):
    """Configuration for MyOperator."""
    my_param: float = 1.0

Nested Configuration

Pipelines can contain nested configs:

@dataclass(frozen=True)
class PipelineConfig:
    preprocessing: PreprocessingPipelineConfig
    alignment: AlignmentConfig
    classification: ClassificationConfig

Configuration Validation

Add validation in __post_init__:

@dataclass(frozen=True)
class ValidatedConfig(OperatorConfig):
    temperature: float = 1.0

    def __post_init__(self) -> None:
        if self.temperature <= 0:
            raise ValueError("temperature must be positive")

Stochastic Operators

If an operator needs stochastic behavior, set stochastic and stream_name in __post_init__ using object.__setattr__() (required because the dataclass is frozen):

@dataclass(frozen=True)
class StochasticOpConfig(OperatorConfig):
    """Configuration for a stochastic operator."""
    dropout_rate: float = 0.1

    def __post_init__(self) -> None:
        object.__setattr__(self, "stochastic", True)
        object.__setattr__(self, "stream_name", "dropout")