fasta_gc.py

# fasta_gc.py
#
# Reads a fasta file and prints out the GC content percentage of each sequence
# in the file
#
# Usage: python fasta_gc.py sequences.fa
#

import sys

def read_fasta_dict(filename):
    """
    Reads sequences from a fasta file, and returns a dictionary that maps the 
    sequence description (key) to the sequence (value) 
    
    For example:
    
    >seq1
    AACCGG
    >seq2
    CCTTTG
    
    would result in {'seq1':'AACCGG','seq2':'CCTTG'}
    
    """
    sequences = {}
    f = open(filename)
    for line in f:
        line = line.strip()
        if '>' in line:
            sequence_name = line # Need to keep track of the name since "line" will change next time
            sequences[sequence_name] = ''
        else:
            # Append to the last sequence
            sequences[sequence_name] = sequences[sequence_name] + line
    f.close()
    return sequences

def gc_content_percent(sequence):
    """
    Calculates the GC-content percentage of the input sequence
    Returns the percentage as an integer out of 100
    """
    gc = sequence.count('G') + sequence.count('C')
    atcg = len(sequence)
    percent_gc = (gc * 100) / atcg
    return percent_gc

def classify_percent(percent):
    if percent < 35:
        classification = 'Low'
    elif percent < 55:
        classification = 'Normal'
    else:
        classification = 'High'
    return classification

def main():
    # Make sure we have a file name
    if len(sys.argv) < 2:
        print('Usage: python', sys.argv[0], '<sequences.fa>')
        exit(1)

    filename = sys.argv[1]

    # Read the sequences into a dictionary
    sequences = read_fasta_dict(filename)

    # Loop over the keys (sequence names) in the dictionary
    for name in sequences:
        sequence = sequences[name]
        percent = gc_content_percent(sequence)
        classification = classify_percent(percent)
        print(percent, classification, name)

main()