import numpy as np
import pandas as pd
from transposonmapper.statistics.dataframe_from_pergene_helpers import (essential_genes,
read_pergene_file, reads_per_insertion)
[docs]def dataframe_from_pergenefile(pergenefile, verbose=True):
"""This function creates a dataframe with the information from a pergene.txt file.
The gene_essentiality is created based on the genes present in the Cerevisiae_EssentialGenes_List_1.txt and Cerevisiae_EssentialGenes_List_2.txt files
The number of reads per insertion (Nreadsperinsrt) is determined by dividing the read_per_gene column by the tn_per_gene column.
Author: Gregory van Beek
Parameters
----------
pergenefile : str
absolute path to the pergene.txt file , one of the outputs of the transposonmapper module
verbose : bool, optional
[description], by default True
Returns
-----------
dataframe
Output is a dataframe where each row is a single gene and with the following columns:
- gene_names
- gene_essentiality
- tn_per_gene
- read_per_gene
- Nreadsperinsrt
"""
# read file
genenames_list,tnpergene_list,readpergene_list,lines=read_pergene_file(pergenefile)
# determine number of reads per insertion per gene
readperinspergene_list=reads_per_insertion(tnpergene_list,readpergene_list,lines)
# determine essential genes
geneessentiality_list=essential_genes(genenames_list,lines)
# create dataframe
read_gene_dict = {"gene_names": genenames_list,
"gene_essentiality": geneessentiality_list,
"tn_per_gene": tnpergene_list,
"read_per_gene": readpergene_list,
"Nreadsperinsrt": readperinspergene_list}
read_gene_df = pd.DataFrame(read_gene_dict, columns = [column_name for column_name in read_gene_dict])
return(read_gene_df)
