ExampleΒΆ
1- Import gtAI functions.
from gtAI import Run_gtAI
from gtAI import gtAI
2- In this example, we will use Saccharomyces cerevisiae S288C coding sequences.
3- Prepare the tRNA gene copy number of the tested genome.
The user has two options; a) input the tRNA gene copy number as python dictionary or, b) using GtRNAdb() function, the user can get it automatically from the GtRNA database, using the link to the tested genome (In our case Saccharomyces cerevisiae S288C). Or by tRNADB_CE() function to get the tRNA gene copy number from tRNADB_CE database using also the link to the tested genome.
In this example, the second option (b) will be used.
url_GtRNAdb = "http://gtrnadb.ucsc.edu/genomes/eukaryota/Scere3/"
#### From GtRNAdb
GtRNA = gtAI.GtRNAdb(url_GtRNAdb)
for more infromation about GtRNAdb() as well as tRNADB_CE(); go to API part.
4- Parameter settings for gtai_analysis() function.
genetic_code_number = 1
ref_fasta = ""
bacteria = False
size_pop = 60
generation_number = 100
for more infromation about gtai_analysis() and the parameters; go to API part.
5- Run gtAI.
df_tai , final_dict_wi, rel_values = Run_gtAI.gtai_analysis(main_fasta,GtRNA,genetic_code_number,bacteria=bacteria, size_pop=size_pop,generation_number=generation_number)
Returns:
df_tai (dataframe): Contains each gene id and its gtAI value
final_dict_wi (dict): Contains each codon and its absolute adaptiveness value
rel_values (dict): Contains each codon and its relative adaptiveness values
6- To save the gtAI result as a CSV file.
import pandas as pd
df_tai.to_csv("test.csv", header=True)