CodonU.correspondence_analysis

Submodules

Package Contents

Functions

build_contingency_table_codon_count(→ pandas.DataFrame)

Creates the contingency table of codon frequency

build_contingency_table_codon_rscu

build_contingency_table_aa_count(→ pandas.DataFrame)

Creates the contingency table of codon frequency

ca_codon(→ prince.CA)

Performs CA on codon frequency or RSCU contingency table

ca_aa

CodonU.correspondence_analysis.build_contingency_table_codon_count(handle: str, genetic_table_num: int, min_len_threshold: int = 200, save_file: bool = False, file_name: str = 'contingency_codon_count', folder_path: str = 'Report') → pandas.DataFrame

Creates the contingency table of codon frequency

Note Gene descriptions are index headings and codons are column headings

Parameters:

  • handle – Handle to the file, or the filename as a string

  • genetic_table_num – Genetic table number for codon table

  • min_len_threshold – Minimum length of nucleotide sequence to be considered as gene

  • save_file – Option for saving the values in xlsx format (Optional)

  • file_name – Intended file name (Optional)

  • folder_path – Folder path where image should be saved (optional)

Returns:

The contingency table as a pandas DataFrame object

CodonU.correspondence_analysis.build_contingency_table_codon_rscu(handle: str, genetic_table_num: int, min_len_threshold: int = 200, save_file: bool = False, file_name: str = 'contingency_codon_rscu', folder_path: str = 'Report') → pandas.DataFrame

Creates the contingency table of codon RSCU

Note Gene descriptions are index headings and codons are column headings

Parameters:

  • handle – Handle to the file, or the filename as a string

  • genetic_table_num – Genetic table number for codon table

  • min_len_threshold – Minimum length of nucleotide sequence to be considered as gene

  • save_file – Option for saving the values in xlsx format (Optional)

  • file_name – Intended file name (Optional)

  • folder_path – Folder path where image should be saved (optional)

Returns:

The contingency table as a pandas DataFrame object

CodonU.correspondence_analysis.build_contingency_table_aa_count(handle: str, genetic_table_num: int, min_len_threshold: int = 66, save_file: bool = False, file_name: str = 'contingency_amino_count', folder_path: str = 'Report') → pandas.DataFrame

Creates the contingency table of codon frequency

Note

  • Protein sequences must have one letter amino acid codes

  • gene descriptions are index headings and aminoacids are column headings

Parameters:

  • handle – Handle to the file, or the filename as a string

  • genetic_table_num – Genetic table number for codon table

  • min_len_threshold – Minimum length of protein sequence to be considered as gene

  • save_file – Option for saving the values in xlsx format (Optional)

  • file_name – Intended file name (Optional)

  • folder_path – Folder path where image should be saved (optional)

Returns:

The contingency table as a pandas DataFrame object

CodonU.correspondence_analysis.ca_codon(contingency_table: pandas.DataFrame, n_components: int = 59, single_syn_codons: list[str] | None = None, save_file: bool = False, file_name: str = 'CA_codon', folder_path: str = 'Report') → prince.CA

Performs CA on codon frequency or RSCU contingency table

Note Gene descriptions must be index headings and codons must column headings of the table

Parameters:

  • contingency_table – The contingency table (pandas DataFrame object)

  • n_components – Components for CA

  • single_syn_codons – List of codons belonging to SF1

  • save_file – Option for saving the values in xlsx format (Optional)

  • file_name – Intended file name (Optional)

  • folder_path – Folder path where image should be saved (optional)

Returns:

The CA object

CodonU.correspondence_analysis.ca_aa(contingency_table: pandas.DataFrame, n_components: int = 20, save_file: bool = False, file_name: str = 'CA_aa', folder_path: str = 'Report') → prince.CA

Performs CA on aa frequency contingency table

Note Gene descriptions must be index headings and aas must column headings of the table

Parameters:

  • contingency_table – The contingency table (pandas DataFrame object)

  • n_components – Components for CA

  • save_file – Option for saving the values in xlsx format (Optional)

  • file_name – Intended file name (Optional)

  • folder_path – Folder path where image should be saved (optional)

Returns:

The CA object