# Lab Worksheet 13¶

## Part 1¶

Write a function that takes two sequences as input, and returns a matrix of scores as we saw in Class 25. You do not have to do the back-tracing, just fill out the matrix.

To get you started, a matrix can be represented in Python as a list of lists. Let's say we want to make a matrix that looks like this:

 1 3 5 7 2 3 4 5 5 2 20 3
In [1]:
# Here's how to make the matrix above from a list of lists
my_matrix = []
# Fill out the 0th row
my_matrix.append([1, 3, 5, 7])
# Fill out the 1st row
my_matrix.append([2, 3, 4, 5])
# Fill out the 2nd row
my_matrix.append([5, 2, 20, 3])

# Here is a helper function to print out matrices
def print_matrix(mat):
# Loop over all rows
for i in range(0, len(mat)):
print("[", end = "")
# Loop over each column in row i
for j in range(0, len(mat[i])):
# Print out the value in row i, column j
print(mat[i][j], end = "")
# Only add a tab if we're not in the last column
if j != len(mat[i]) - 1:
print("\t", end = "")
print("]\n")

print_matrix(my_matrix)

# To retrieve the value from the 2nd row, in the 0th column, is relatively simple:
print("The value in the 2nd row and the 0th column is:", my_matrix[2][0])

# The format is always my_matrix[row][column].

[1	3	5	7]

[2	3	4	5]

[5	2	20	3]

The value in the 2nd row and the 0th column is: 5


### Part 1 Hints¶

Break the problem down into as many small steps as possible. Here are a few hints:

• Before you calculate any scores, make an empty matrix of the appropriate size using the zeros() function defined below.
• Fill out the 0th row and 0th column before you calculate any other scores.
• The max() function will return the maximum value from a list of values. For example max(1,7,3) will return 7.
• Make liberal use of the range() function.
• Use the print_matrix() function to print out your matrix as frequently as possible. Always make sure that your code is doing what you think it's doing!
• Remember, in Python, we start counting from 0.
In [2]:
# Use these values to calculate scores
gap_penalty = -1
match_award = 1
mismatch_penalty = -1

# Make a score matrix with these two sequences
seq1 = "ATTACA"
seq2 = "ATGCT"

# A function for making a matrix of zeroes
def zeros(rows, cols):
# Define an empty list
retval = []
# Set up the rows of the matrix
for x in range(rows):
# For each row, add an empty list
retval.append([])
# Set up the columns in each row
for y in range(cols):
# Add a zero to each column in each row
retval[-1].append(0)
# Return the matrix of zeros
return retval

# A function for determining the score between any two bases in alignment
def match_score(alpha, beta):
if alpha == beta:
return match_award
elif alpha == '-' or beta == '-':
return gap_penalty
else:
return mismatch_penalty

# The function that actually fills out a matrix of scores
def needleman_wunsch(seq1, seq2):

# length of two sequences
n = len(seq1)
m = len(seq2)

# Generate matrix of zeros to store scores
score = zeros(m+1, n+1)

########################
########################

# Use the following steps as a guide to calculate the score matrix

# 1. Fill out first column

# 2. Fill out first row

# 3. Fill out all other values in the score matrix

# Return the final score matrix
return score

# Test out the needleman_wunsch() function
print_matrix(needleman_wunsch(seq1, seq2))

[0	0	0	0	0	0	0]

[0	0	0	0	0	0	0]

[0	0	0	0	0	0	0]

[0	0	0	0	0	0	0]

[0	0	0	0	0	0	0]

[0	0	0	0	0	0	0]



## Part 2: If that was easy...¶

Modify your code from Part 1 to back-trace through the score matrix and print out the final alignment. HINT: For the back-tracing, you'll want to use a while loop (or several of them).

In [3]:
def needleman_wunsch(seq1, seq2):

# Store length of two sequences
n = len(seq1)
m = len(seq2)

# Generate matrix of zeros to store scores
score = zeros(m+1, n+1)

# Calculate score table

# Create variables to store alignment
align1 = ""
align2 = ""

# Back-trace from bottom right of the score matrix and compute the alignment

return(align1, align2)

output1, output2 = needleman_wunsch(seq1, seq2)

print(output1 + "\n" + output2)




In [ ]: