additional_python_quiz_1.txt

#1. 

def get_position_indices(triplet, dna):  
    """
    This function finds the presence/number of occurence of a triplet code within a DNA sequence

    Parameters: 
    triplet (str): 3-code sequence
    DNA (str): The DNA sequence

    Returns:
    list: A list containing the index position where the triplet occurs in the DNA sequences
    
    """
    # Create an empty list to store the resulting position/index list
    position_list = []  
    # Split the DNA sequence into 3-letter codes
    triplet_list = [dna[i:i+3] for i in range(0, len(dna), 3)]  
    # For loop to iterate through the DNA sequence
    for x in range(0, len(triplet_list), 1):      
        # If statement to check for the presence of the query triplet
        if triplet == triplet_list[x]:            
            # append the list position of the triplet if it is present
            position_list.append(x) 
    # return the output        
    return position_list

get_p = get_position_indices ('GAA', 'CCGGAAGAGCTTACTTAG')
print (get_p)

#2.

# The phrase to search for
phrase = "will"

# The file to search in
filename = "Downloads/conclusions.txt"

try:
    # Open the file
    with open(filename, 'r') as grep_file:  
        # For statement to iterate though the file, line by line, telling it to start at line 1, since there is no line 0
        for line_number, line in enumerate(grep_file, start=1): 
            # If statement to check if the query phrase is present in a line
            if phrase in line: 
                # Print the matching line with its number
                print(f"Line {line_number}: {line.strip()}")  
# If file does not exist: specific exception handler code
except FileNotFoundError:
    print(f"The file '{filename}' does not exist.")
# General exception handler code
except Exception as e:
    print(f"An error occurred: {e}")


#3.

def grep_python_cmd(phrase, filename):
    """
    Performs the same function as the UNIX grep command.

    Parameters:
    phrase (str): The phrase to search for.
    filename (str): The filename (file path) to search in or iterate through.
    """
    # create an empty list to store each line where the hit occurs
    hits = []
    try:
        # Open the file
        with open(filename, 'r') as grep_file:  
            # For statement to iterate through the file
            for line_number, line in enumerate(grep_file, start=1): 
                # If statement to check if the query phrase is present in a line
                if phrase in line: 
                    # Print the matching line with its number
                    print(f"Line {line_number}: {line.strip()}")  
                    hits.append(line.strip())  # Store the matching line in hits
    # If file does not exist: specific exception handler code
    except FileNotFoundError:
        print(f"The file '{filename}' does not exist.")
    # General exception handler code
    except Exception as e:
        print(f"An error occurred: {e}")
    
    return hits 

# The file to search in
filename = "Downloads/conclusions.txt"

# Example
grep_python_cmd("will", filename)


# 4.
def dna_to_rna(dna_seq):
    """
    Converts DNA sequences to RNA

    Function parameters:
    dna_seq (str): DNA sequences

    Returns:
    RNA sequence
    """
    # Create a variable to hold the resulting RNA sequence 
    rna_sequence = ""
    # For Loop to iterate through the DNA sequence
    for base in dna_seq:
        # If statement to convert Thymine in DNA to Uracil
        if base == 'T':
            rna_sequence += 'U'
        else:
            rna_sequence += base
    return rna_sequence

# Example
dna = "ATGCTGCATGCAAATCGCCTATCGTACTAGGCATGC"
rna = dna_to_rna(dna)
print(f"DNA: {dna}")
print(f"RNA: {rna}")



#5.

# Paste the alignment from Canvas
align ='''seq_1: ATGCGCTGCATGCATTGCATGCATG
                 |||| || |||| ||||| || |||
          seq_2: ATGCTCTCCATGTATTGCNTGGATG'''

# Split the alignment into individual lines
lines = align.split('\n')

# Parse the sequences
seq1 = lines[0].split(':')[1].strip()
seq2 = lines[2].split(':')[1].strip()

# Parse the sequence names
name1 = lines[0].split(':')[0].strip()
name2 = lines[2].split(':')[0].strip()

# Create the FASTA format using the required symbols and line spacing
fasta_content = f">{name1}\n{seq1}\n>{name2}\n{seq2}"

# Save to a FASTA file
output_file = "alignment.fasta"
with open(output_file, "w") as fasta_align:
    fasta_align.write(fasta_content)

print(f"FASTA file saved as {output_file}")

#6.
# sample sequence
cyt_b = "TTTTTGAGGAGCTACTGTAATTACAAATTTAATATCAGCAATTCCATTAATTGGTAATGAAATTGTAACTTGATTATGAGGAGGATTTAGAGTTAATAATGCAACATTAAATCGATTTTACTCTTTACATTTTATTATACCATTTGTAATTTTAATAATAATTTTAATCCATTTAATAACTTTACATTTAACAGGGTCTAACAATCCTTTAGGAACAAATAGAAATTTATATAAAATTCCTTTTCATTTTTATTTTACAGTAAAAGATATACAAGGGTTTTTATTTATAATTGTTAGATTATTATTATTATGTTGTTTTATTCCTTATATTTTAGGAGATCCAGAAAATTTTAATATAGCTAATCCAATAATTACTCCCATTCATATTCAGCCTGAATGATATTTCTTATTTGCATATGCAATTTTACGATCA"

# To extract index position 100 and 150 (inclusive)
extracted_section = cyt_b[99:150]  
print("Extracted section:", extracted_section)


#7. 

def calculate_similarity(string1, string2):
    """
    Function to compare two strings and calculate the similarity score.

    Parameters:
    string1 (str): The first string to compare.
    string2 (str): The second string to compare.

    Returns:
    float: The similarity score.
    """
    # A crude comparison, which is what I did requires both sequences (str) to have
    # the same length, else one'd need to factor in things like gaps, gap penalty, and gap extension
    if len(string1) != len(string2):
        raise ValueError("Strings must be of the same length.")

    # Count the number of exact positional matches
    matches = sum(1 for a, b in zip(string1, string2) if a == b)

    # Calculate the similarity score as the proportion of invariant sites
    similarity_score = matches / len(string1) # the length of either string could be used, seeing as they're similar

    return similarity_score

# Example usage
string_1 = 'AGGAGGCGGCGTGGTGCGTACGATGCGCAGGGTATTCACTAGAAAGCTAG'
string_2 = 'CCTCTCTGGCTGACCTCCATAGCTCCTAAGGGGCGATGGAGGGCTCCAAG'

similarity = calculate_similarity(string_1, string_2)
print(f"Similarity score: {similarity}")

#8.
It's saying I don't have access to view this resource.


#9. 
# Create function
def RE_sequence (sequence, enzyme):
    """
    Cuts the given DNA sequence at restriction enzyme sites and returns a list of fragment lengths.
    
    Parameters 
    sequence (str): The DNA sequence to be cut.
    enzyme (str): The restriction site (string) where the enzyme cuts.
    
    Returns:
    List of fragment lengths.
    """
    # Split/cut the dna sequence at the enzyme recognition site
    fragments = sequence.split(enzyme)  
    # Estimate the fragment length as a list
    fragment_lengths = [len(fragment) for fragment in fragments]  
    
    return fragment_lengths

# Example
seq_1 = "ATGCGTCGTCTGACGTATCCCTGTGCAAGTCATCCGTCGTCTGACGTATCTCTGTGCATGTCATAAGTCGTCTGACGTATCGGTGTGCCCGTCATGCGTCGTCTGACGTATGCGTGTGCAAGTCATATTTCGTCTGACGTATCACTGTGCAGGTCAGGGGTCGTCTGACGTATTTTTGTGCACGTC"
enzyme = "TAT"

fragment_lengths = RE_sequence (seq_1, enzyme)
print(fragment_lengths)

#10.
# List variables containing the names and the correspoding ages
names_list = ['Jim', 'Jeff', 'Geoff', 'Grace', 'George', 'Julie', 'Justine', 'Jemima']
age_list = ['22', '34', '46', '58', '70', '19', '35', '64']

# Create a function to combine both names and ages in both Lists
def combine_lists(list1, list2):
    """
    A function to combine the name and corresponding age of each individual from 2 lists

    Parameters:
    list1: a list containing the names
    list2: a list containing the ages

    Returns:
    A dictionary containing the name as the key and the age as the value
    """
    # If statement to ensure that both lists are of the same length or size
    if len(list1) != len(list2):
        raise ValueError("Lists must have the same size") # error message if the sizes differ
    # Else statement to iterate through the lists if they're of similar sizes
    else:
        # create an empty dictionary to store the output
        comb_dict = {}
        # For loop to iterate through list1 index positions starting from the position zero or the first index 
        # through the entire length of list1
        for x in range(0, len(list1), 1):
            # list1 is defined as the Key, while list2 is defined as the value
            comb_dict[list1[x]] = (list2[x])
        # returns the dictionary
    return comb_dict

# the function is called using the name list and age list 
combine_lists(names_list, age_list)