pyproteonet.io.maxquant.load_maxquant
- pyproteonet.io.maxquant.load_maxquant(peptides_table: DataFrame | str | Path, samples: List[str] | None = None, protein_groups_table: DataFrame | str | Path | None = None, protein_group_value_columns: List[str] = ['Intensity'], peptide_value_columns: List[str] = ['Intensity'], peptide_columns: List[str] = ['Sequence'], protein_group_columns: List[str] = ['Fasta headers'], missing_value: float = 0, peptide_protein_group_map_column: str = 'Protein group IDs', remove_invalid_mappings: bool = False) Dataset
Loads a dataset given in MaxQuant format (experimental for now). Might not support all datsets.
- Parameters:
protein_groups_table (Union[pd.DataFrame, str, Path]) – Pandas dataframe or path to proteinGroups.txt.
peptides_table (Union[pd.DataFrame, str, Path]) – Pandas dataframe or path to peptides.txt.
samples (List[str], optional) – List of sample names to load (must be present as columns in peptides.txt and proteinGroups.txt).
protein_group_value_columns (List[str], optional) – Values to load for every protein group and sample. Sample name and value column will be concatenated to a column name which is then looked up n the peptides table. Defaults to [“Intensity”].
peptide_value_columns (List[str], optional) – Values to load for every protein group and sample. Sample name and value column will be concatenated to a column name which is then looked up in the protein groups table. Defaults to [“Intensity”].
peptide_columns (List[str], optional) – Columns from the peptides table to keep as meta info per molecule. Defaults to [“Sequence”].
protein_group_columns (List[str], optional) – Columns from the protein group table to keep as meta info per molecule. Defaults to [“Fasta headers”].
missing_vlue (float, optional) – Value interpreted as missing, Defaults to 0.
- Returns:
The loaded Dataset.
- Return type: