coretex.entities.dataset.sequence_dataset.sequence_dataset.SequenceDataset Class Reference

Inheritance diagram for coretex.entities.dataset.sequence_dataset.sequence_dataset.SequenceDataset:

Public Member Functions
Optional[Self]	createSequenceDataset (cls, str name, int projectId, Union[Path, str] metadataPath, Optional[Dict[str, Any]] meta=None)
None	download (self, bool decrypt=True, bool ignoreCache=False)
bool	isPairedEnd (self)
Public Member Functions inherited from coretex.entities.dataset.network_dataset.NetworkDataset
Path	path (self)
Self	fetchCachedDataset (cls, List[str] dependencies)
Self	createDataset (cls, str name, int projectId, Optional[Dict[str, Any]] meta=None)
str	generateCacheName (cls, str prefix, List[str] dependencies)
Self	createCacheDataset (cls, str prefix, List[str] dependencies, int projectId)
bool	finalize (self)
bool	rename (self, str name)
SampleType	add (self, Union[Path, str] samplePath, Optional[str] sampleName=None, **Any metadata)
Public Member Functions inherited from coretex.entities.dataset.dataset.Dataset
int	count (self)
Optional[SampleType]	getSample (self, str name)

Detailed Description

    Sequence Dataset class which is used for Datasets whose
    samples contain sequence data (.fasta, .fastq)

Definition at line 33 of file sequence_dataset.py.

Member Function Documentation

createSequenceDataset()

Optional[Self] coretex.entities.dataset.sequence_dataset.sequence_dataset.SequenceDataset.createSequenceDataset	(		cls,
		str	name,
		int	projectId,
		Union[Path, str]	metadataPath,
		Optional[Dict[str, Any]]	meta = None
	)

    Creates a new sequence dataset with the provided name and metadata

    Parameters
    ----------
    name : str
        dataset name
    projectId : int
        project for which the dataset will be created
    metadataPath : Union[Path, str]
        path the zipped metadata file

    Returns
    -------
    The created sequence dataset object or None if creation failed

    Example
    -------
    >>> from coretex import SequenceDataset
    \b
    >>> dummyDataset = SequenceDataset.createSequenceDataset("dummyDataset", 123, pathToMetadata)
    >>> if dummyDataset is not None:
            print("Dataset created successfully")

Definition at line 64 of file sequence_dataset.py.

    ) -> Optional[Self]:
 
        """
            Creates a new sequence dataset with the provided name and metadata
 
            Parameters
            ----------
            name : str
                dataset name
            projectId : int
                project for which the dataset will be created
            metadataPath : Union[Path, str]
                path the zipped metadata file
 
            Returns
            -------
            The created sequence dataset object or None if creation failed
 
            Example
            -------
            >>> from coretex import SequenceDataset
            \b
            >>> dummyDataset = SequenceDataset.createSequenceDataset("dummyDataset", 123, pathToMetadata)
            >>> if dummyDataset is not None:
                    print("Dataset created successfully")
        """
 
        if isinstance(metadataPath, str):
            metadataPath = Path(metadataPath)
 
        dataset = cls.createDataset(name, projectId, meta)
 
        if dataset.isEncrypted:
            dataset.metadata = _encryptedSampleImport(CustomSample, "_metadata", metadataPath, dataset.id, getProjectKey(dataset.projectId))
        else:
            dataset.metadata = _chunkSampleImport(CustomSample, "_metadata", metadataPath, dataset.id)
 
        return dataset
 

download()

None coretex.entities.dataset.sequence_dataset.sequence_dataset.SequenceDataset.download	(		self,
		bool	decrypt = True,
		bool	ignoreCache = False
	)

    Downloads dataset from Coretex

    Parameters
    ----------
    ignoreCache : bool
        if dataset is already downloaded and ignoreCache
        is True it will be downloaded again (not required)

    Example
    -------
    >>> from coretex import NetworkDataset
    \b
    >>> dummyDataset = NetworkDataset.fetchById(1023)
    >>> dummyDataset.download()

Reimplemented from coretex.entities.dataset.network_dataset.NetworkDataset.

Definition at line 109 of file sequence_dataset.py.

    def download(self, decrypt: bool = True, ignoreCache: bool = False) -> None:
        super().download(decrypt, ignoreCache)
 
        self.metadata.download(decrypt, ignoreCache)
 

isPairedEnd()

bool coretex.entities.dataset.sequence_dataset.sequence_dataset.SequenceDataset.isPairedEnd

(

self

)

    This function returns True if the dataset holds paired-end reads and
    False if it holds single end. Files for paired-end reads must contain
    "_R1_" and "_R2_" in their names, otherwise an exception will be raised.
    If the sample contains gzip compressed sequences, you will have to call
    Sample.unzip method first otherwise calling Sample.isPairedEnd will
    raise an exception

    Raises
    ------
    FileNotFoundError -> if no files meeting the requirements for either single-end
        or paired-end sequencing reads
    ValueError -> if dataset has a combination of single-end and paired-end samples

Definition at line 114 of file sequence_dataset.py.

    def isPairedEnd(self) -> bool:
        """
            This function returns True if the dataset holds paired-end reads and
            False if it holds single end. Files for paired-end reads must contain
            "_R1_" and "_R2_" in their names, otherwise an exception will be raised.
            If the sample contains gzip compressed sequences, you will have to call
            Sample.unzip method first otherwise calling Sample.isPairedEnd will
            raise an exception
 
            Raises
            ------
            FileNotFoundError -> if no files meeting the requirements for either single-end
                or paired-end sequencing reads
            ValueError -> if dataset has a combination of single-end and paired-end samples
        """
 
        pairedEndSamples = [sample.isPairedEnd() for sample in self.samples]
 
        if all(pairedEndSamples):
            return True
 
        if not any(pairedEndSamples):
            return False
 
        raise ValueError(">> [Coretex] Dataset contains a mix of paired-end and single-end sequences. It should contain either one or the other")
 

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The documentation for this class was generated from the following file:

• coretex/entities/dataset/sequence_dataset/sequence_dataset.py