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Problem 2 of this homework is due on April 30, 2019 at 4:00pm. Please submit Part 2 as a PDF file on Canvas. Before submission, please re-run all cells by clicking "Kernel" and selecting "Restart & Run All."
Problem 1 is due, on paper, within the first ten minutes of lab on May 1, 2019. Problem 1 should not contain any code!
Problem 1 (5 points): Using Smith-Waterman (not Needleman-Wunsch!), align the following two sequences by hand:
ACCAG
ACAAGTDraw out a score matrix, with the back-tracing arrows, using the following scoring function:
Match: +2
Mismatch: -1
Gap: -2After you have filled out your score matrix, be sure to write out the final alignment or alignments.
Problem 2 (5 points): Modify the code from the Lab 13 Worksheet, Part 1 so that it runs the Smith-Waterman algorithm. Several helper functions are provided for you below. Your function final should produce the matrix of scores only. You do not need to do back-tracing. Use the same scoring function as in Problem 1.
Run the sequences from Problem 1 through your function and print the output using print_matrix().
# Use these values to calculate scores
match_award = 2
mismatch_penalty = -1
gap_penalty = -2
# Make a score matrix with these two sequences
seq1 = "ACCAG"
seq2 = "ACAAGT"
# 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")
# 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 smith_waterman(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)
########################
# Your code goes here
########################
return score
print_matrix(smith_waterman(seq1, seq2))