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Double Digest through Regular Expression in python

I have the following DNA sequence in dna.txt file :

ATGGCAATAACCCCCCGTTTCTACTTCTAGAGGAGAAAAGTATTGACATGAGCGCTCCCGGCACAAGGGCCAAAGAAGTCTCCAATTTCTTATTTCCGAATGACATGCGTCTCCTTGCGGGTAAATCACCGACCGCAATTCATAGAAGCCTGGGGGAACAGATAGGTCTAATTAGCTTAAGAGAGTAAATCCTGGGATCATTCAGTAGTAACCATAAACTTACGCTGGGGCTTCTTCGGCGGATTTTTACAGTTACCAACCAGGAGATTTGAAGTAAATCAGTTGAGGATTTAGCCGCGCTATCCGGTAATCTCCAAATTAAAACATACCGTTCCATGAAGGCTAGAATTACTTACCGGCCTTTTCCATGCCTGCGCTATACCCCCCCACTCTCCCGCTTATCCGTCCGAGCGGAGGCAGTGCGATCCTCCGTTAAGATATTCTTACGTGTGACGTAGCTATGTATTTTGCAGAGCTGGCGAACGCGTTGAACACTTCACAGATGGTAGGGATTCGGGTAAAGGGCGTATAATTGGGGACTAACATAGGCGTAGACTACGATGGCGCCAACTCAATCGCAGCTCGAGCGCCCTGAATAACGTACTCATCTCAACTCATTCTCGGCAATCTACCGAGCGACTCGATTATCAACGGCTGTCTAGCAGTTCTAATCTTTTGCCAGCATCGTAATAGCCTCCAAGAGATTGATGATAGCTATCGGCACAGAACTGAGACGGCGCCGATGGATAGCGGACTTTCGGTCAACCACAATTCCCCACGGGACAGGTCCTGCGGTGCGCATCACTCTGAATGTACAAGCAACCCAAGTGGGCCGAGCCTGGACTCAGCTGGTTCCTGCGTGAGCTCGAGACTCGGGATGACAGCTCTTTAAACATAGAGCGGGGGCGTCGAACGGTCGAGAAAGTCATAGTACCTCGGGTACCAACTTACTCAGGTTATTGCTTGAAGCTGTACTATTTTAGGGGGGGAGCGCTGAAGGTCTCTTCTTCTCATGACTGAACTCGCGAGGGTCGTGAAGTCGGTTCCTTCAATGGTTAAAAAACAAAGGCTTACTGTGCGCAGAGGAACGCCCATCTAGCGGCTGGCGTCTTGAATGCTCGGTCCCCTTTGTCATTCCGGATTAATCCATTTCCCTCATTCACGAGCTTGCGAAGTCTACATTGGTATATGAATGCGACCTAGAAGAGGGCGCTTAAAATTGGCAGTGGTTGATGCTCTAAACTCCATTTGGTTTACTCGTGCATCACCGCGATAGGCTGACAAAGGTTTAACATTGAATAGCAAGGCACTTCCGGTCTCAATGAACGGCCGGGAAAGGTACGCGCGCGGTATGGGAGGATCAAGGGGCCAATAGAGAGGCTCCTCTCTCACTCGCTAGGAGGCAAATGTAAAACAATGGTTACTGCATCGATACATAAAACATGTCCATCGGTTGCCCAAAGTGTTAAGTGTCTATCACCCCTAGGGCCGTTTCCCGCATATAAACGCCAGGTTGTATCCGCATTTGATGCTACCGTGGATGAGTCTGCGTCGAGCGCGCCGCACGAATGTTGCAATGTATTGCATGAGTAGGGTTGACTAAGAGCCGTTAGATGCGTCGCTGTACTAATAGTTGTCGACAGACCGTCGAGATTAGAAAATGGTACCAGCATTTTCGGAGGTTCTCTAACTAGTATGGATTGCGGTGTCTTCACTGTGCTGCGGCTACCCATCGCCTGAAATCCAGCTGGTGTCAAGCCATCCCCTCTCCGGGACGCCGCATGTAGTGAAACATATACGTTGCACGGGTTCACCGCGGTCCGTTCTGAGTCGACCAAGGACACAATCGAGCTCCGATCCGTACCCTCGACAAACTTGTACCCGACCCCCGGAGCTTGCCAGCTCCTCGGGTATCATGGAGCCTGTGGTTCATCGCGTCCGATATCAAACTTCGTCATGATAAAGTCCCCCCCTCGGGAGTACCAGAGAAGATGACTACTGAGTTGTGCGAT

I want to read the DNA sequence from the file dna.txt and then predict the lengths of the fragments that we will get by digesting the sequence with the (made-up) restriction enzymes

  • AbcI: cutting site "ANT*AAT"
  • AbcII: cutting site "GCRW*TG"

asterisks indicate where the enzyme cuts the DNA

Can anyone solve my query?

regex resriction-enzyme python
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updated by Ram Ram • written by anasjamshed anasjamshed

Did you try anything? Biostars is generally not a code-writing service.

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written by ATpoint ATpoint 
import re

# open input file
infile = open("dna.txt")
line = infile.read()
# split line by "," into list of strings
sequence = line.strip().split(",")

print(sequence)

after that, I am unable to do?

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updated by Ram Ram • written by anasjamshed anasjamshed

It is something diffrent

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written by anasjamshed anasjamshed

Like the other user said, those answers should be useful, not applicable as-is. Try adapting them and come back to us if you have difficulties.

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written by Ram Ram

2 answers

Here's something to get you started:

import re
def digdigest(digseq, cutsite_orig):
  cutsite_l, cutsite_r = re.split("\*", cutsite_orig)

  #Identify cutting positions with a unique character
  cutsite = re.sub("\*", "", cutsite_orig)
  cutsite

  #If there are Ns in the cutsite, replace this with the . regex placeholder
  cutsite = re.sub("N", ".", cutsite)
  cutsite_l = re.sub("N", ".", cutsite_l)
  cutsite_r = re.sub("N", ".", cutsite_r)

  #cutsite_l+"__"+cutsite_r
  digseq_mod = re.sub(r"("+cutsite_l+")"+"("+cutsite_r+")", r"\1__\2", digseq)



  print(digseq_mod.split("__"))
  #return(digseq_mod.split("__"))

Provide digdigest() the sequence and cutting site as you have indicated in the OP, and you'll get something like this:

digdigest("ATATATATAGTAATGTGTGCATTAATATGC", "ANT*AAT")
#['ATATATATAGT', 'AATGTGTGCATT', 'AATATGC']
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written by Dunois • Dunois

i have tried this script:

import re
dna = open("dna.txt").read().strip("\n")
#print(str(len(dna)))
all_cuts = [0]

# finda and append different cut positions for AbcI
for match in re.finditer(r"A[ATGC]TAAT", dna):#begins with A followed by any one character [ATGC]and then TAAT
    all_cuts.append(match.start() + 3) #ANT*AAT, finding position is A therefore +3 for ANT
print(all_cuts)

# add cut positions for AbcII
for match in re.finditer(r"GC[AG][AT]TG", dna):
    all_cuts.append(match.start() + 4) # GCRW*TG the finding position is G therefore +4 for GCRW, 
print(all_cuts)

# add the finalend position i.e. length of dna
all_cuts.append(len(dna))
sorted_cuts = sorted(all_cuts)# Sort the cut position in ascending order so that we get length of each fragements correct
print(sorted_cuts)
for i in range(1,len(sorted_cuts)):
    this_cut_position = sorted_cuts[i]
    previous_cut_position = sorted_cuts[i-1]
    fragment_size = this_cut_position - previous_cut_position
    print("one fragment size is " + str(fragment_size))

And it gives me the following output :

[0, 1143, 1628]
[0, 1143, 1628, 488, 1577]
[0, 488, 1143, 1577, 1628, 2012]
one fragment size is 488
one fragment size is 655
one fragment size is 434
one fragment size is 51
one fragment size is 384
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written by anasjamshed anasjamshed

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