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#!/usr/bin/python3
'''
Created 2012
Contains various help functions which read or produce an input/ output
@author: Sven Giese
'''
import os
import random
import HTSeq
def readdna(filename):
"""
Reads in the dna sequence of the given fasta
@type filename: string
@param filename: Fasta-file used as input.
@rtype: HTSeq Sequence object
@return: Reference Fasta.
"""
chr = HTSeq.FastaReader(filename)
for fasta in chr:
referenz = HTSeq.Sequence(fasta.seq,fasta.name)
return(referenz)
def writefile(sequenceObject,filename):
"""
Writes a given sequence object to a fasta file.
@type sequenceObject: HTSeq Sequence object
@param sequenceObject: Reference sequence as fasta.
"""
outfasta = open(filename,"w")
sequenceObject.write_to_fasta_file(outfasta)
outfasta.close()
def writeoverview(Ndic_G,aadic_G,Ndic_AR,aadic_AR,filename):
"""
Creates the "delta" file for the comparison of the two chromosoms. This file contains the differences in nucleotide distribution between reference and artificial.
input: nucleotid dictionary genom, aa dictionary genome, nucleotid dictionary artificial chromosom, aa dictionary, filename
@type Ndic_G: dictionary
@param Ndic_G: Nucleotid dictionary genom.
@type aadic_G: dictionary
@param aadic_G: AA dictionary genome.
@type Ndic_AR: dictionary
@param Ndic_AR: Nucleotid dictionary artificial.
@type aadic_AR: dictionary
@param aadic_AR: AA dictionary artificial
@type filename: string
@param filename: Output filename.
"""
fobj = open(filename,"w")
fobj.write("NUC /AA \t Genom \t Artificial Reference \t Delta \n")
sum1 =0
sum2= 0
for item in list(Ndic_G.keys()):
fobj.write(item +"\t"+str(Ndic_G[item])+"\t"+str(Ndic_AR[item])+"\t"+str(Ndic_G[item]-Ndic_AR[item])+"\n")
sum1 +=abs(Ndic_G[item]-Ndic_AR[item])
fobj.write(str(sum1)+"\n")
for item in list(aadic_G.keys()):
fobj.write(item +"\t"+str(aadic_G[item])+"\t"+str(aadic_AR[item])+"\t"+str(aadic_G[item]-aadic_AR[item])+"\n")
sum2 +=abs(aadic_G[item]-aadic_AR[item])
fobj.write(str(sum2)+"\n")
def nucleotide_dist_seq(seq,txt_file,shallwrite):
"""
Writes the nucleotide distribution in a file and returns the dictionary. adjust s for % results.
@type seq: string
@param seq: Nucleotide sequence.
@type txt_file: string
@param txt_file: Output compare file.
@type shallwrite: Bool
@param shallwrite: Decides if percentages values are written to the output.
"""
Nndic={"A":0,"C":0,"G":0,"T":0,"N":0}
seq = seq.decode()
for i in range(0,len(seq)):
Nndic[seq[i]]+=1
s=len(seq)
s=1
if (shallwrite==1):
output_file=open(txt_file,'w')
for item in list(Nndic.keys()):
Nndic[item]=Nndic[item]/float(s)
output_file.write(item + "\t" + str(Nndic[item])+"\n")
output_file.close()
else:
for item in list(Nndic.keys()):
Nndic[item]=Nndic[item]/float(s)
return (Nndic) #N can be used for checking: should be the same number in real
# and artificial chromosome
def aa_dist_seq(seq,txt_file,shallwrite):
"""
Writes the AA distribution in a file and returns the dictionary. adjust s for % results.
@type seq: string
@param seq: Nucleotide sequence.
@type txt_file: string
@param txt_file: Output compare file.
@type shallwrite: Bool
@param shallwrite: Write output in percentages..
"""
aadic = {"A":0,"R":0,"N":0,"D":0,"C":0,"E":0,"Q":0,"G":0,"H":0,"I":0,"L":0,"K":0,"M":0,"F":0,"P":0,"S":0,"T":0,"W":0,"Y":0,"V":0,"*":0}
for i in range(0,len(seq)):
'''escape 'n' Sequences '''
if (seq[i] in aadic):
aadic[seq[i]]+=1
else:
continue
n = len(seq)
n=1
if (shallwrite==1):
output_file=open(txt_file,'w')
for item in list(aadic.keys()):
aadic[item]=aadic[item]/float(n)
output_file.write(item + "\t" + str(aadic[item])+"\n")
output_file.close()
else:
for item in list(aadic.keys()):
aadic[item]=aadic[item]/float(n)
return (aadic)
'''
input: DNA Sequence, outputfilename and 1/0 for writing/not writing outputfile '''
def nucleotide_dist_file(file_fasta,txt_file):
"""
Writes the DNA distribution in a file and returns the dictionary. adjust n for % results
@type file_fasta: string
@param file_fasta: DNA Sequence
@type txt_file: string
@param txt_file: Filename for output.
"""
input_file=open(file_fasta,'r')
output_file=open(txt_file,'a')
seq=''
for line in input_file:
if line[0]!='>':
line=line.rstrip()
seq+=line
output_file.write(str(nucleotide_dist_seq(seq)))
output_file.write('\n')
output_file.close()
input_file.close()
'''gets the number of missmatches between 2 sequences
input: orig sequence, decoy sequence '''
def gethammingdistance(original,artificial):
"""
Calculates the hamming distances between two sequences.
@type original: list
@param original: Nucleotide sequence from the reference.
@type artificial: list
@param artificial: Nucleotide sequence from the artificial reference.
"""
hamming = 0
not_hamming=0
for i in range(0,len(original)):
if (original[i]!=artificial[i]):
hamming +=1
else:
not_hamming+=1
print(("#hamming distance REF-ART\t"+ str(hamming)))
if hamming == 0:
print("avg. distance:\tnan")
else:
print(("avg. distance:\t" + str(len(original)/float(hamming))))
print("###########################\r\n")
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