import pandas as pd
from immuneML.IO.dataset_import.DataImport import DataImport
from immuneML.IO.dataset_import.DatasetImportParams import DatasetImportParams
from immuneML.data_model.dataset import Dataset
from immuneML.data_model.receptor.RegionType import RegionType
from immuneML.util.ImportHelper import ImportHelper
from scripts.specification_util import update_docs_per_mapping
[docs]class OLGAImport(DataImport):
"""
Imports data generated by `OLGA <https://github.com/statbiophys/OLGA>`_ simulations into a Repertoire-, or SequenceDataset. Assumes that the columns in each
file correspond to: nucleotide sequences, amino acid sequences, v genes, j genes
Reference: Sethna, Zachary et al.
‘High-throughput immune repertoire analysis with IGoR’. Bioinformatics, (2019)
`doi.org/10.1093/bioinformatics/btz035 <https://doi.org/10.1093/bioinformatics/btz035>`_.
Arguments:
path (str): This is the path to a directory with OLGA files to import. By default path is set to the current working directory.
is_repertoire (bool): If True, this imports a RepertoireDataset. If False, it imports a SequenceDataset.
By default, is_repertoire is set to True.
metadata_file (str): Required for RepertoireDatasets. This parameter specifies the path to the metadata file.
This is a csv file with columns filename, subject_id and arbitrary other columns which can be used as labels in instructions.
Only the OLGA files included under the column 'filename' are imported into the RepertoireDataset.
SequenceDataset metadata is currently not supported.
import_illegal_characters (bool): Whether to import sequences that contain illegal characters, i.e., characters
that do not appear in the sequence alphabet (amino acids including stop codon '*', or nucleotides). When set to false, filtering is only
applied to the sequence type of interest (when running immuneML in amino acid mode, only entries with illegal
characters in the amino acid sequence are removed). By default import_illegal_characters is False.
import_empty_nt_sequences (bool): imports sequences which have an empty nucleotide sequence field; can be True or False.
By default, import_empty_nt_sequences is set to True.
import_empty_aa_sequences (bool): imports sequences which have an empty amino acid sequence field; can be True or False; for analysis on
amino acid sequences, this parameter should be False (import only non-empty amino acid sequences). By default, import_empty_aa_sequences is set to False.
region_type (str): Which part of the sequence to import. By default, this value is set to IMGT_CDR3. This means the
first and last amino acids are removed from the CDR3 sequence, as OLGA uses the IMGT junction. Specifying
any other value will result in importing the sequences as they are.
Valid values for region_type are the names of the :py:obj:`~immuneML.data_model.receptor.RegionType.RegionType` enum.
separator (str): Column separator, for OLGA this is by default "\\t".
YAML specification:
.. indent with spaces
.. code-block:: yaml
my_olga_dataset:
format: OLGA
params:
path: path/to/files/
is_repertoire: True # whether to import a RepertoireDataset (True) or a SequenceDataset (False)
metadata_file: path/to/metadata.csv # metadata file for RepertoireDataset
import_illegal_characters: False # remove sequences with illegal characters for the sequence_type being used
import_empty_nt_sequences: True # keep sequences even though the nucleotide sequence might be empty
import_empty_aa_sequences: False # filter out sequences if they don't have sequence_aa set
# Optional fields with OLGA-specific defaults, only change when different behavior is required:
separator: "\\t" # column separator
region_type: IMGT_CDR3 # what part of the sequence to import
"""
[docs] @staticmethod
def import_dataset(params: dict, dataset_name: str) -> Dataset:
return ImportHelper.import_dataset(OLGAImport, params, dataset_name)
[docs] @staticmethod
def alternative_load_func(filepath, params):
df = pd.read_csv(filepath, sep=params.separator, iterator=False, dtype=str, header=None)
df.columns = ["sequences", "sequence_aas", "v_genes", "j_genes"]
return df
[docs] @staticmethod
def preprocess_dataframe(df: pd.DataFrame, params: DatasetImportParams):
if "sequences" not in df.columns and "sequence_aas" not in df.columns:
raise IOError("OLGAImport: Columns should contain at least 'sequences' or 'sequence_aas'.")
if "counts" not in df.columns:
df["counts"] = 1
df["sequence_identifiers"] = None
ImportHelper.drop_empty_sequences(df, params.import_empty_aa_sequences, params.import_empty_nt_sequences)
ImportHelper.drop_illegal_character_sequences(df, params.import_illegal_characters)
ImportHelper.junction_to_cdr3(df, params.region_type)
ImportHelper.update_gene_info(df)
ImportHelper.load_chains(df)
return df
[docs] @staticmethod
def get_documentation():
doc = str(OLGAImport.__doc__)
region_type_values = str([region_type.name for region_type in RegionType])[1:-1].replace("'", "`")
mapping = {
"Valid values for region_type are the names of the :py:obj:`~immuneML.data_model.receptor.RegionType.RegionType` enum.": f"Valid values are {region_type_values}.",
}
doc = update_docs_per_mapping(doc, mapping)
return doc