CodonU.analyzer.tRNA_comp

Module Contents

Functions

get_anticodon_count_dict(→ dict[str, int])

Retrieves the anticodon table from given link

calculate_gtai(→ tuple[pandas.DataFrame, ...)

Calculates the gtAI value for each gene according to Anwar et al., 2023
CodonU.analyzer.tRNA_comp.get_anticodon_count_dict(url: str, database: str) → dict[str, int]

Retrieves the anticodon table from given link

NOTE: The database can have only two values, i.e. “tRNADB_CE” and “GtRNAdb”
Parameters:

  • url – URL to anticodon table

  • database – Type of database from the above options

Returns:

The dictionary containing anticodon as key and count as val

Raises:

UnsupportedDatabase – If database has other values than mentioned

CodonU.analyzer.tRNA_comp.calculate_gtai(handle: str, anticodon_dict: dict, genetic_code_num: int, reference: str | None = None, size_pop: int = 60, generation_num: int = 100, save_file: bool = False, file_name: str = 'tAI_report', folder_path: str = 'Report') → tuple[pandas.DataFrame, pandas.DataFrame, pandas.DataFrame]

Calculates the gtAI value for each gene according to Anwar et al., 2023

The function returns following dataframes:

  • tai_df: The dataframe contains gene description and tAI values

  • abs_wi_df: The dataframe contains each anticodon and absolute weights according to the paper

  • rel_wi_df: The dataframe contains each anticodon and relative weights according to the paper

Note: The function will generate a file named ‘best_fit.py’

param handle:

Path to the fasta file as a string

param anticodon_dict:

The dictionary containing anticodon as key and count as value

param genetic_code_num:

Genetic table number for codon table

param reference:

Path to the reference fasta file as a string (Optional)

param size_pop:

A parameter for the genetic algorithm to identify the population size (Optional)

param generation_num:

A parameter for the genetic algorithm to identify the generation number (Optional)

param save_file:

Option for saving the values in xlsx format (Optional)

param file_name:

Intended file name (Optional)

param folder_path:

Folder path where image should be saved (optional)

return:

A tuple of 3 dataframes, as discussed earlier

raises FileExistsError:

If re-write permission is not given for the file best_fit.py

raises ImportError:

If best_fit.py is not created or deleted after creation