dae.annotation package

Submodules

dae.annotation.annotatable module

class dae.annotation.annotatable.Annotatable(chrom: str, pos: int, pos_end: int, annotatable_type: Type)

Bases: object

Base class for annotatables used in annotation pipeline.

class Type(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

Defines annotatable types.

COMPLEX = 5

LARGE_DELETION = 7

LARGE_DUPLICATION = 6

POSITION = 0

REGION = 1

SMALL_DELETION = 4

SMALL_INSERTION = 3

SUBSTITUTION = 2

static from_string(variant: str) → Type

Construct annotatable type from string argument.

property chrom: str

property chromosome: str

property end_position: int

static from_string(value: str) → Annotatable

Deserialize an Annotatable instance from a string value.

property pos: int

property pos_end: int

property position: int

static tokenize(value: str) → tuple[str, list[str]]

class dae.annotation.annotatable.CNVAllele(chrom: str, pos_begin: int, pos_end: int, cnv_type: Type)

Bases: Annotatable

Defines copy number variants annotatable.

static from_string(value: str) → CNVAllele

Deserialize an Annotatable instance from a string value.

class dae.annotation.annotatable.Position(chrom: str, pos: int)

Bases: Annotatable

Annotatable class representing a single position in a chromosome.

static from_string(value: str) → Position

Deserialize an Annotatable instance from a string value.

class dae.annotation.annotatable.Region(chrom: str, pos_begin: int, pos_end: int)

Bases: Annotatable

Annotatable class representing a region in a chromosome.

static from_string(value: str) → Region

Deserialize an Annotatable instance from a string value.

class dae.annotation.annotatable.VCFAllele(chrom: str, pos: int, ref: str, alt: str)

Bases: Annotatable

Defines small variants annotatable.

property alt: str

property alternative: str

static from_string(value: str) → VCFAllele

Deserialize an Annotatable instance from a string value.

property ref: str

property reference: str

dae.annotation.annotate_columns module

dae.annotation.annotate_columns.cli(raw_args: list[str] | None = None) → None

Entry point for running the columns annotation tool.

dae.annotation.annotate_doc module

dae.annotation.annotate_doc.cli(raw_args: list[str] | None = None) → None

Run command line interface for annotate_vcf tool.

dae.annotation.annotate_doc.configure_argument_parser() → ArgumentParser

Construct and configure argument parser.

dae.annotation.annotate_utils module

dae.annotation.annotate_utils.add_input_files_to_task_graph(args: dict, task_graph: TaskGraph) → None

dae.annotation.annotate_utils.build_output_path(raw_input_path: str, output_path: str | None) → str

Build an output filepath for an annotation tool’s output.

dae.annotation.annotate_utils.cache_pipeline_resources(grr: GenomicResourceRepo, pipeline: AnnotationPipeline) → None

Cache resources that the given pipeline will use.

dae.annotation.annotate_utils.get_stuff_from_context(cli_args: dict[str, Any]) → tuple[AnnotationPipeline, GenomicContext, GenomicResourceRepo]

Helper method to collect necessary objects from the genomic context.

dae.annotation.annotate_utils.produce_partfile_paths(input_file_path: str, regions: list[Region], work_dir: str) → list[str]

Produce a list of file paths for output region part files.

dae.annotation.annotate_utils.produce_regions(pysam_file: TabixFile, region_size: int) → list[Region]

Given a region size, produce contig regions to annotate by.

dae.annotation.annotate_utils.produce_tabix_index(filepath: str, args: dict | None = None) → None

Produce a tabix index file for the given variants file.

dae.annotation.annotate_utils.stringify(value: Any, *, vcf: bool = False) → str

Format the value to a string for human-readable output.

dae.annotation.annotate_vcf module

dae.annotation.annotate_vcf.cli(raw_args: list[str] | None = None) → None

Entry point for running the VCF annotation tool.

dae.annotation.annotation_config module

class dae.annotation.annotation_config.AnnotationConfigParser

Bases: object

Parser for annotation configuration.

static has_wildcard(string: str) → bool

Ascertain whether a string contains a valid wildcard.

static match_labels_query(query: dict[str, str], resource_labels: dict[str, str]) → bool

Check if the labels query for a wildcard matches.

static parse_complete(raw: dict[str, Any], idx: int, grr: GenomicResourceRepo | None = None) → list[AnnotatorInfo]

Parse a full-form annotation config.

static parse_minimal(raw: str, idx: int) → AnnotatorInfo

Parse a minimal-form annotation config.

static parse_raw(pipeline_raw_config: list[dict[str, Any]] | RawFullConfig | None, grr: GenomicResourceRepo | None = None) → tuple[AnnotationPreamble | None, list[AnnotatorInfo]]

Parse raw dictionary annotation pipeline configuration.

static parse_raw_attribute_config(raw_attribute_config: dict[str, Any]) → AttributeInfo

Parse annotation attribute raw configuration.

static parse_raw_attributes(raw_attributes_config: Any) → list[AttributeInfo]

Parse annotator pipeline attribute configuration.

static parse_short(raw: dict[str, Any], idx: int, grr: GenomicResourceRepo | None = None) → list[AnnotatorInfo]

Parse a short-form annotation config.

static parse_str(content: str, source_file_name: str | None = None, grr: GenomicResourceRepo | None = None) → tuple[AnnotationPreamble | None, list[AnnotatorInfo]]

Parse annotation pipeline configuration string.

static query_resources(annotator_type: str, wildcard: str, grr: GenomicResourceRepo) → list[str]

Collect resources matching a given query.

exception dae.annotation.annotation_config.AnnotationConfigurationError

Bases: ValueError

class dae.annotation.annotation_config.AnnotationPreamble(summary: 'str', description: 'str', input_reference_genome: 'str', input_reference_genome_res: 'GenomicResource | None', metadata: 'dict[str, Any]')

Bases: object

description: str

input_reference_genome: str

input_reference_genome_res: GenomicResource | None

metadata: dict[str, Any]

summary: str

class dae.annotation.annotation_config.AnnotatorInfo(_type: str, attributes: list[AttributeInfo], parameters: ParamsUsageMonitor | dict[str, Any], documentation: str = '', resources: list[GenomicResource] | None = None, annotator_id: str = 'N/A')

Bases: object

Defines annotator configuration.

annotator_id: str

attributes: list[AttributeInfo]

documentation: str = ''

parameters: ParamsUsageMonitor

resources: list[GenomicResource]

type: str

class dae.annotation.annotation_config.AttributeInfo(name: str, source: str, *, internal: bool, parameters: ParamsUsageMonitor | dict[str, Any], _type: str = 'str', description: str = '', documentation: str | None = None)

Bases: object

Defines annotation attribute configuration.

static create(source: str, name: str | None = None, *, internal: bool = False) → AttributeInfo

Create an AttributeInfo instance.

description: str = ''

property documentation: str

internal: bool

name: str

parameters: ParamsUsageMonitor

source: str

type: str = 'str'

class dae.annotation.annotation_config.ParamsUsageMonitor(data: dict[str, Any])

Bases: Mapping

Class to monitor usage of annotator parameters.

get_unused_keys() → set[str]

get_used_keys() → set[str]

class dae.annotation.annotation_config.RawFullConfig

Bases: TypedDict

annotators: list[dict[str, Any]]

preamble: RawPreamble

class dae.annotation.annotation_config.RawPreamble

Bases: TypedDict

description: str

input_reference_genome: str

metadata: dict[str, Any]

summary: str

dae.annotation.annotation_factory module

Factory for creation of annotation pipeline.

dae.annotation.annotation_factory.build_annotation_pipeline(config: list[dict[str, Any]] | RawFullConfig, grr: GenomicResourceRepo, *, allow_repeated_attributes: bool = False, work_dir: Path | None = None, config_old_raw: str | None = None, full_reannotation: bool = False) → AnnotationPipeline

Build an annotation pipeline.

dae.annotation.annotation_factory.check_for_repeated_attributes_in_annotator(annotator_config: AnnotatorInfo) → None

Check for repeated attributes in annotator configuration.

dae.annotation.annotation_factory.check_for_repeated_attributes_in_pipeline(pipeline: AnnotationPipeline, *, allow_repeated_attributes: bool = False) → None

Check for repeated attributes in pipeline configuration.

dae.annotation.annotation_factory.check_for_unused_parameters(info: AnnotatorInfo) → None

Check annotator configuration for unused parameters.

dae.annotation.annotation_factory.copy_annotation_pipeline(pipeline: AnnotationPipeline) → AnnotationPipeline

Copy an annotation pipeline instance.

dae.annotation.annotation_factory.copy_reannotation_pipeline(pipeline: ReannotationPipeline) → ReannotationPipeline

Copy a reannotation pipeline instance.

dae.annotation.annotation_factory.get_annotator_factory(annotator_type: str) → Callable[[AnnotationPipeline, AnnotatorInfo], Annotator]

Find and return a factory function for creation of an annotator type.

If the specified annotator type is not found, this function raises ValueError exception.

Returns:

the annotator factory for the specified annotator type.

Raises:

ValueError – when can’t find an annotator factory for the specified annotator type.

dae.annotation.annotation_factory.get_available_annotator_types() → list[str]

Return the list of all registered annotator factory types.

dae.annotation.annotation_factory.load_pipeline_from_file(raw_path: str, grr: GenomicResourceRepo, *, allow_repeated_attributes: bool = False, work_dir: Path | None = None) → AnnotationPipeline

Load an annotation pipeline from a configuration file.

dae.annotation.annotation_factory.load_pipeline_from_yaml(raw: str, grr: GenomicResourceRepo, *, allow_repeated_attributes: bool = False, work_dir: Path | None = None) → AnnotationPipeline

Load an annotation pipeline from a YAML-formatted string.

dae.annotation.annotation_factory.register_annotator_factory(annotator_type: str, factory: Callable[[AnnotationPipeline, AnnotatorInfo], Annotator]) → None

Register additional annotator factory.

By default all genotype storage factories should be registered at [dae.genotype_storage.factories] extenstion point. All registered factories are loaded automatically. This function should be used if you want to bypass extension point mechanism and register addition genotype storage factory programatically.

dae.annotation.annotation_factory.resolve_repeated_attributes(pipeline: AnnotationPipeline, repeated_attributes: set[str]) → None

Resolve repeated attributes in pipeline configuration via renaming.

dae.annotation.annotation_pipeline module

Provides annotation pipeline class.

class dae.annotation.annotation_pipeline.AnnotationPipeline(repository: GenomicResourceRepo)

Bases: object

Provides annotation pipeline abstraction.

add_annotator(annotator: Annotator) → None

annotate(annotatable: Annotatable | None, context: dict | None = None) → dict

Apply all annotators to an annotatable.

batch_annotate(annotatables: Sequence[Annotatable | None], contexts: list[dict] | None = None, batch_work_dir: str | None = None) → list[dict]

Apply all annotators to a list of annotatables.

build_pipeline_genomic_context() → GenomicContext

Create a genomic context from the pipeline parameters.

close() → None

Close the annotation pipeline.

get_annotator_by_attribute_info(attribute_info: AttributeInfo) → Annotator | None

get_attribute_info(attribute_name: str) → AttributeInfo | None

get_attributes() → list[AttributeInfo]

get_info() → list[AnnotatorInfo]

get_resource_ids() → set[str]

open() → AnnotationPipeline

Open all annotators in the pipeline and mark it as open.

print() → None

Print the annotation pipeline.

class dae.annotation.annotation_pipeline.Annotator(pipeline: AnnotationPipeline | None, info: AnnotatorInfo)

Bases: ABC

Annotator provides a set of attrubutes for a given Annotatable.

abstract annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

property attributes: list[AttributeInfo]

batch_annotate(annotatables: Sequence[Annotatable | None], contexts: list[dict[str, Any]], batch_work_dir: str | None = None) → Iterable[dict[str, Any]]

close() → None

get_info() → AnnotatorInfo

is_open() → bool

open() → Annotator

property resource_ids: set[str]

property resources: list[GenomicResource]

property used_context_attributes: tuple[str, ...]

class dae.annotation.annotation_pipeline.AnnotatorDecorator(child: Annotator)

Bases: Annotator

Defines annotator decorator base class.

close() → None

is_open() → bool

open() → Annotator

class dae.annotation.annotation_pipeline.FullReannotationPipeline(pipeline_new: AnnotationPipeline, pipeline_old: AnnotationPipeline)

Bases: ReannotationPipeline

Special-case ReannotationPipeline.

Completely removes all old attributes and runs every new annotator, without reusing anything.

class dae.annotation.annotation_pipeline.InputAnnotableAnnotatorDecorator(child: Annotator)

Bases: AnnotatorDecorator

Defines annotator decorator to use input annotatable if defined.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

static decorate(child: Annotator) → Annotator

property used_context_attributes: tuple[str, ...]

class dae.annotation.annotation_pipeline.ReannotationPipeline(pipeline_new: AnnotationPipeline, pipeline_old: AnnotationPipeline)

Bases: AnnotationPipeline

Special pipeline that handles reannotation of a previous pipeline.

AnnotationDependencyGraph

alias of dict[AnnotatorInfo, list[tuple[AnnotatorInfo, AttributeInfo]]]

annotate(annotatable: Annotatable | None, context: dict | None = None) → dict

Apply all annotators to an annotatable.

static build_dependency_graph(pipeline: AnnotationPipeline) → AnnotationDependencyGraph

Make dependency graph for an annotation pipeline.

get_attributes() → list[AttributeInfo]

get_dependencies_for(info: AnnotatorInfo) → set[AnnotatorInfo]

Get all dependencies for a given annotator.

get_dependents_for(info: AnnotatorInfo) → set[AnnotatorInfo]

Get all dependents for a given annotator.

print() → None

Print the annotation pipeline.

class dae.annotation.annotation_pipeline.ValueTransformAnnotatorDecorator(child: Annotator, value_transformers: dict[str, Callable[[Any], Any]])

Bases: AnnotatorDecorator

Define value transformer annotator decorator.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

static decorate(child: Annotator) → Annotator

Apply value transform decorator to an annotator.

dae.annotation.annotator_base module

Provides base class for annotators.

class dae.annotation.annotator_base.AnnotatorBase(pipeline: AnnotationPipeline | None, info: AnnotatorInfo, source_type_desc: dict[str, tuple[str, str]])

Bases: Annotator

Base implementation of the Annotator class.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

batch_annotate(annotatables: Sequence[Annotatable | None], contexts: list[dict[str, Any]], batch_work_dir: str | None = None) → list[dict[str, Any]]

open() → Annotator

dae.annotation.cnv_collection_annotator module

class dae.annotation.cnv_collection_annotator.CnvCollectionAnnotator(pipeline: AnnotationPipeline, info: AnnotatorInfo)

Bases: Annotator

Simple effect annotator class.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

close() → None

open() → Annotator

dae.annotation.cnv_collection_annotator.build_cnv_collection_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

dae.annotation.debug_annotator module

class dae.annotation.debug_annotator.HelloWorldAnnotator(pipeline: AnnotationPipeline, info: AnnotatorInfo)

Bases: Annotator

Defines example annotator.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

dae.annotation.debug_annotator.build_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

Create an example hello world annotator.

dae.annotation.docker_annotator module

class dae.annotation.docker_annotator.DockerAnnotator(pipeline: AnnotationPipeline | None, info: AnnotatorInfo)

Bases: AnnotatorBase

Base class for annotators that use docker containers.

open() → Annotator

abstract run(**kwargs: Any) → None

dae.annotation.effect_annotator module

class dae.annotation.effect_annotator.EffectAnnotatorAdapter(pipeline: AnnotationPipeline, info: AnnotatorInfo)

Bases: AnnotatorBase

Adapts effect annotator to be used in annotation infrastructure.

close() → None

open() → Annotator

dae.annotation.effect_annotator.build_effect_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

dae.annotation.gene_score_annotator module

Module containing the gene score annotator.

class dae.annotation.gene_score_annotator.GeneScoreAnnotator(pipeline: AnnotationPipeline | None, info: AnnotatorInfo, gene_score_resource: GenomicResource, input_gene_list: str)

Bases: Annotator

Gene score annotator class.

DEFAULT_AGGREGATOR_TYPE = 'dict'

aggregate_gene_values(score_id: str, gene_symbols: list[str], aggregator_type: str) → Any

Aggregate gene score values.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

property used_context_attributes: tuple[str, ...]

dae.annotation.gene_score_annotator.build_gene_score_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

Create a gene score annotator.

dae.annotation.gene_set_annotator module

class dae.annotation.gene_set_annotator.GeneSetAnnotator(pipeline: AnnotationPipeline | None, info: AnnotatorInfo, gene_set_resource: GenomicResource, input_gene_list: str)

Bases: AnnotatorBase

Gene set annotator class.

property used_context_attributes: tuple[str, ...]

dae.annotation.gene_set_annotator.build_gene_set_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

Create a gene set annotator.

dae.annotation.genomic_context module

class dae.annotation.genomic_context.CLIAnnotationContextProvider

Bases: CLIGenomicContextProvider

Defines annotation pipeline genomics context provider.

static add_argparser_arguments(parser: ArgumentParser) → None

Add command line arguments to the argument parser.

static init(**kwargs: Any) → GenomicContext | None

Build a CLI genomic context.

dae.annotation.genomic_context.get_context_pipeline(context: GenomicContext) → AnnotationPipeline | None

Construct an annotation pipeline.

dae.annotation.liftover_annotator module

Provides a lift over annotator and helpers.

class dae.annotation.liftover_annotator.AbstractLiftoverAnnotator(pipeline: AnnotationPipeline | None, info: AnnotatorInfo, chain: LiftoverChain, source_genome: ReferenceGenome, target_genome: ReferenceGenome)

Bases: AnnotatorBase

Liftovver annotator class.

close() → None

liftover_allele(allele: VCFAllele) → VCFAllele | None

Liftover an allele.

liftover_cnv(cnv_allele: Annotatable) → Annotatable | None

Liftover CNV allele annotatable.

liftover_position(position: Annotatable) → Annotatable | None

Liftover position annotatable.

liftover_region(region: Annotatable) → Annotatable | None

Liftover region annotatable.

open() → Annotator

class dae.annotation.liftover_annotator.BasicLiftoverAnnotator(pipeline: AnnotationPipeline | None, info: AnnotatorInfo, chain: LiftoverChain, source_genome: ReferenceGenome, target_genome: ReferenceGenome)

Bases: AbstractLiftoverAnnotator

Basic liftover annotator class.

class dae.annotation.liftover_annotator.BcfLiftoverAnnotator(pipeline: AnnotationPipeline | None, info: AnnotatorInfo, chain: LiftoverChain, source_genome: ReferenceGenome, target_genome: ReferenceGenome)

Bases: AbstractLiftoverAnnotator

BCF tools liftover re-implementation annotator class.

dae.annotation.liftover_annotator.basic_liftover_allele(chrom: str, pos: int, ref: str, alt: str, liftover_chain: LiftoverChain, source_genome: ReferenceGenome, target_genome: ReferenceGenome) → tuple[str, int, str, str] | None

Basic liftover an allele.

dae.annotation.liftover_annotator.basic_liftover_variant(chrom: str, pos: int, ref: str, alts: list[str], liftover_chain: LiftoverChain, source_genome: ReferenceGenome, target_genome: ReferenceGenome) → tuple[str, int, str, list[str]] | None

Basic liftover variant utility function.

dae.annotation.liftover_annotator.bcf_liftover_allele(chrom: str, pos: int, ref: str, alt: str, liftover_chain: LiftoverChain, source_genome: ReferenceGenome, target_genome: ReferenceGenome) → tuple[str, int, str, str] | None

Liftover a variant.

dae.annotation.liftover_annotator.bcf_liftover_variant(chrom: str, pos: int, ref: str, alts: list[str], liftover_chain: LiftoverChain, source_genome: ReferenceGenome, target_genome: ReferenceGenome) → tuple[str, int, str, list[str]] | None

BCF liftover variant utility function.

dae.annotation.liftover_annotator.build_liftover_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

Create a liftover annotator.

dae.annotation.normalize_allele_annotator module

Provides normalize allele annotator and helpers.

class dae.annotation.normalize_allele_annotator.NormalizeAlleleAnnotator(pipeline: AnnotationPipeline, info: AnnotatorInfo)

Bases: AnnotatorBase

Annotator to normalize VCF alleles.

close() → None

open() → Annotator

dae.annotation.normalize_allele_annotator.build_normalize_allele_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

dae.annotation.normalize_allele_annotator.normalize_allele(allele: VCFAllele, genome: ReferenceGenome) → VCFAllele

Normalize an allele.

Using algorithm defined in following https://genome.sph.umich.edu/wiki/Variant_Normalization

dae.annotation.processing_pipeline module

class dae.annotation.processing_pipeline.Annotation(annotatable: ~dae.annotation.annotatable.Annotatable | None, context: dict[str, ~typing.Any] = <factory>)

Bases: object

A pair of an annotatable and its relevant context.

The context can hold any key/value pair relevant to the annotatable and is typically used to store the results of annotators.

annotatable: Annotatable | None

context: dict[str, Any]

class dae.annotation.processing_pipeline.AnnotationPipelineAnnotatablesBatchFilter(annotation_pipeline: AnnotationPipeline)

Bases: AnnotationsWithSourceBatchFilter, AnnotationPipelineContextManager

Filter that annotates an AnnotationWithSource batch using a pipeline.

class dae.annotation.processing_pipeline.AnnotationPipelineAnnotatablesFilter(annotation_pipeline: AnnotationPipeline)

Bases: AnnotationsWithSourceFilter, AnnotationPipelineContextManager

Filter that annotates an AnnotationWithSource object using a pipeline.

class dae.annotation.processing_pipeline.AnnotationPipelineContextManager(annotation_pipeline: AnnotationPipeline)

Bases: AbstractContextManager

A context manager for annotation pipelines.

class dae.annotation.processing_pipeline.AnnotationsWithSource(source: Any, annotations: list[Annotation])

Bases: object

A pair of a list of Annotation instances and their source.

The source is typically a variant read from some format, with the ‘annotations’ attribute corresponding to its alleles.

annotations: list[Annotation]

source: Any

class dae.annotation.processing_pipeline.AnnotationsWithSourceBatchFilter

Bases: Filter

Base class for filters that work on AnnotationsWithSource batches.

filter(data: Sequence[AnnotationsWithSource]) → Sequence[AnnotationsWithSource]

Filter a batch of AnnotationsWithSource objects.

class dae.annotation.processing_pipeline.AnnotationsWithSourceFilter

Bases: Filter

Base class for filters that work on AnnotationsWithSource objects.

filter(data: AnnotationsWithSource) → AnnotationsWithSource

Filter a single AnnotationsWithSource object.

class dae.annotation.processing_pipeline.DeleteAttributesFromAWSBatchFilter(attributes_to_remove: Sequence[str])

Bases: Filter

Filter to remove items from AWS batches. Works in-place.

filter(data: Sequence[AnnotationsWithSource]) → Sequence[AnnotationsWithSource]

class dae.annotation.processing_pipeline.DeleteAttributesFromAWSFilter(attributes_to_remove: Sequence[str])

Bases: Filter

Filter to remove items from AWSs. Works in-place.

filter(data: AnnotationsWithSource) → AnnotationsWithSource

dae.annotation.reannotate_instance module

class dae.annotation.reannotate_instance.ReannotateInstanceTool(raw_args: list[str] | None = None, gpf_instance: GPFInstance | None = None)

Bases: object

Annotation tool to reannotate the configured GPF instance

get_argument_parser() → ArgumentParser

Construct and configure argument parser.

run() → None

Run the tool.

dae.annotation.reannotate_instance.cli(raw_args: list[str] | None = None, gpf_instance: GPFInstance | None = None) → None

Entry point method for instance reannotation tool.

dae.annotation.record_to_annotatable module

class dae.annotation.record_to_annotatable.CSHLAlleleRecordToAnnotatable(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: RecordToAnnotable

Transform a CSHL variant record into a VCF allele annotatable.

build(record: dict[str, str]) → Annotatable

class dae.annotation.record_to_annotatable.DaeAlleleRecordToAnnotatable(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: RecordToAnnotable

Transform a CSHL variant record into a VCF allele annotatable.

build(record: dict[str, str]) → Annotatable

class dae.annotation.record_to_annotatable.RecordToAnnotable(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: ABC

Base class for record to annotable transformation.

abstract build(record: dict[str, str]) → Annotatable

class dae.annotation.record_to_annotatable.RecordToCNVAllele(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: RecordToAnnotable

Transform a columns record into a CNV allele annotatable.

build(record: dict[str, str]) → Annotatable

class dae.annotation.record_to_annotatable.RecordToPosition(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: RecordToAnnotable

build(record: dict[str, str]) → Annotatable

class dae.annotation.record_to_annotatable.RecordToRegion(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: RecordToAnnotable

build(record: dict[str, str]) → Annotatable

class dae.annotation.record_to_annotatable.RecordToVcfAllele(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: RecordToAnnotable

build(record: dict[str, str]) → Annotatable

class dae.annotation.record_to_annotatable.VcfLikeRecordToVcfAllele(columns: tuple, ref_genome: ReferenceGenome | None)

Bases: RecordToAnnotable

Transform a columns record into VCF allele annotatable.

build(record: dict[str, str]) → Annotatable

dae.annotation.record_to_annotatable.add_record_to_annotable_arguments(parser: ArgumentParser) → None

dae.annotation.record_to_annotatable.build_record_to_annotatable(parameters: dict[str, str], available_columns: set[str], ref_genome: ReferenceGenome | None = None) → RecordToAnnotable

Transform a variant record into an annotatable.

dae.annotation.score_annotator module

This contains the implementation of the three score annotators.

Genomic score annotators defined are positions_score, np_score, and allele_score.

class dae.annotation.score_annotator.AlleleScoreAnnotator(pipeline: AnnotationPipeline, info: AnnotatorInfo)

Bases: GenomicScoreAnnotatorBase

This class implements allele_score annotator.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

build_score_aggregator_documentation(attr_info: AttributeInfo) → list[str]

Collect score aggregator documentation.

class dae.annotation.score_annotator.GenomicScoreAnnotatorBase(pipeline: AnnotationPipeline, info: AnnotatorInfo, score: GenomicScore)

Bases: Annotator

Genomic score base annotator.

add_score_aggregator_documentation(attribute_info: AttributeInfo, aggregator: str, attribute_conf_agg: str | None) → None

Collect score aggregator documentation.

abstract build_score_aggregator_documentation(attr_info: AttributeInfo) → list[str]

Construct score aggregator documentation.

close() → None

is_open() → bool

open() → Annotator

class dae.annotation.score_annotator.PositionScoreAnnotator(pipeline: AnnotationPipeline, info: AnnotatorInfo)

Bases: GenomicScoreAnnotatorBase

This class implements the position_score annotator.

The position_score annotator requires the resrouce_id parameter, whose value must be an id of a genomic resource of type position_score.

The position_score resource provides a set of scores (see …) that the position_score annotator uses as attributes to assign to the annotatable.

The position_score annotator recognized one attribute level parameter called position_aggregator that controls how the position scores are aggregator for annotates that ref to a region of the reference genome.

annotate(annotatable: Annotatable | None, context: dict[str, Any]) → dict[str, Any]

Produce annotation attributes for an annotatable.

build_score_aggregator_documentation(attr_info: AttributeInfo) → list[str]

Collect score aggregator documentation.

dae.annotation.score_annotator.build_allele_score_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

dae.annotation.score_annotator.build_np_score_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

dae.annotation.score_annotator.build_position_score_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

dae.annotation.score_annotator.get_genomic_resource(pipeline: AnnotationPipeline, info: AnnotatorInfo, resource_types: set[str]) → GenomicResource

Return genomic score resource used for given genomic score annotator.

dae.annotation.simple_effect_annotator module

class dae.annotation.simple_effect_annotator.SimpleEffectAnnotator(pipeline: AnnotationPipeline, info: AnnotatorInfo)

Bases: AnnotatorBase

Simple effect annotator class.

call_region(chrom: str, beg: int, end: int, transcripts: list[TranscriptModel], func_name: str, classification: str) → tuple[str, set[str]] | None

Call a region with a specific classification.

cds_intron_regions(transcript: TranscriptModel) → list[Region]

Return whether region is CDS intron.

noncoding_regions(transcript: TranscriptModel) → list[Region]

Return whether the region is noncoding.

open() → Annotator

peripheral_regions(transcript: TranscriptModel) → list[Region]

Return whether the region is peripheral.

run_annotate(chrom: str, beg: int, end: int) → tuple[str, set[str]]

Return classification with a set of affected genes.

utr_regions(transcript: TranscriptModel) → Sequence[Region]

Return whether the region is classified as UTR.

dae.annotation.simple_effect_annotator.build_simple_effect_annotator(pipeline: AnnotationPipeline, info: AnnotatorInfo) → Annotator

Module contents