Commit 0ff1395b authored by Toby Hodges's avatar Toby Hodges
Browse files

added complete version of DNA stats script

parent d1c25941
#! /usr/bin/env python
'''This script counts nucleotides in sequences in
a DNA FASTA file, prints the content of each sequence
and the G/C content too.'''
from sys import argv
# command_line_arguments = argv[1:]
# program_name = argv[0]
# print(program_name)
# print(command_line_arguments)
filename = argv[1]
handle = open(filename, 'r')
for line in handle.readlines():
line = line.strip()
if line[0] == '>': # find header/description lines
print(line)
nucleotides = {'A': 0,
'C': 0,
'G': 0,
'T': 0}
else:
for l in line:
nucleotides[l] += 1
print('nucleotide content:')
for nucleotide in nucleotides:
print('%s: %d' % (nucleotide, nucleotides[nucleotide]))
c = nucleotides['C']
g = nucleotides['G']
a = nucleotides['A']
t = nucleotides['T']
GC_content = float(c + g) / (c + g + a + t)
print(GC_content)
handle.close()
from argparse import ArgumentParser # tool for parsing command line arguments
# load in special type of dictionary that remembers the order of its keys
from collections import OrderedDict
from sys import stderr, stdout # objects for writing to STDERR and STDOUT
def calculate_GC(nucleotide_counts):
'''Given a dictionary of nucleotide counts, such as the second-level
dictionaries returned from count_letter(), calculate G/C content and return
it as a percentage.
Usage:
calculate_GC(count_dict) -> float'''
c_count = nucleotide_counts['C']
g_count = nucleotide_counts['G']
total_length = sum(nucleotide_counts.values())
# use float() to make the % calculation compatible with python version 2
percentage_GC = (float(c_count + g_count) / total_length) * 100
return percentage_GC
def count_letters(filename, alphabet='DNA'):
'''Counts the frequency of each letter in each sequence contained in a
FASTA file. Returns a dictionary of dictionaries keyed by sequence ID string.
Each nested dictionary contains letter:count pairs for the respective sequence.
Usage:
count_letters(file_name, alphabet='DNA') -> dict
alphabet str from ['DNA','RNA','PROTEIN' ]
'''
_alphabets = {'DNA': list('ACGT'),
'RNA': list('ACGU'),
'PROTEIN': list('ARNDBCEQZGHILKMFPSTWYV')}
try: # use try:except blocks to perform simple tests and specify error behaviour
_alphabet_letters = _alphabets[alphabet.upper()]
except KeyError: # define what should happen when an unexpected key is used
raise KeyError("Unexpected alphabet: {}. Must be one of: 'DNA', 'RNA', 'PROTEIN'".format(alphabet)) # custom error message to help user understand what went wrong
sequence_counts = OrderedDict()
with open(filename, 'r') as handle:
for line in handle.readlines():
line = line.strip()
if line[0] == '>': # find header/description lines
id_string = line.lstrip('>') # remove > from start of seq header
sequence_counts[id_string] = OrderedDict( (l,0) for l in _alphabet_letters ) # initialise count for this sequence, with an OrderedDictionary built from a for-loop written onto a single line
ignored = {} # initialise an empty dictionary to capture any unexpected letters
else: # if not a header line, must be a sequence line, so count the letters
for letter in line.upper():
if letter not in _alphabet_letters: # capture non-alphabet letters
if letter in ignored:
ignored[letter] += 1
else:
stderr.write( # print message for logging/debugging
'ignoring unexpected letter {} found in sequence {}\n'.
format(letter, id_string))
ignored[letter] = 1
else:
sequence_counts[id_string][letter] += 1
if ignored: # print counts for ignored letters, useful for later debugging
stderr.write('ignored letter counts for {}:\n{}\n'.format(
id_string,
'\n'.join(['{}: {}'.format(k, v) for k,v in ignored.items()])
))
return sequence_counts
# create argument parser to manage interface
parser = ArgumentParser(description='''Count the nucleotides
in each sequence in a DNA FASTA file, and print a summary of
the content of each sequence, and the G/C % too.''')
parser.add_argument('fasta', # positional argument(s) for input file(s)
metavar='FASTA',
type=str,
nargs='+',
help='A file of DNA sequences in FASTA format')
parser.add_argument('-g', '--GC', # option for calculating G/C content
action='store_true', # this is a boolean (true/false) option, which should store a 'True' value if specified on the command line
help='calculate GC content for DNA sequences')
args = parser.parse_args()
files = args.fasta # get the FASTA file name(s) from the command line arguments
# loop through all provided files and calculate the stats...
for filename in files:
stdout.write('\nGetting counts for file {}\n'.format(
filename))
# call count_letters function defined above
counts = count_letters(filename, 'DNA')
# for each
for seq_id, count_dict in counts.items():
stdout.write('{}\n'.format(seq_id)) # write sequence id to STDOUT
for letter, count in count_dict.items():
stdout.write('{}\t{}\n'.format(letter, count)) # counts to STDOUT
if args.GC:
# call the calculate_GC function defined above
GC_content = calculate_GC(count_dict)
# use {:.2} to insert percentage into string with two decimal places of precision
stdout.write('GC content:\t{:.2f}%\n'.format(GC_content))
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