Calculate the Hamming difference between two DNA strands.
A mutation is simply a mistake that occurs during the creation or copying of a nucleic acid, in particular DNA. Because nucleic acids are vital to cellular functions, mutations tend to cause a ripple effect throughout the cell. Although mutations are technically mistakes, a very rare mutation may equip the cell with a beneficial attribute. In fact, the macro effects of evolution are attributable by the accumulated result of beneficial microscopic mutations over many generations.
The simplest and most common type of nucleic acid mutation is a point mutation, which replaces one base with another at a single nucleotide.
By counting the number of differences between two homologous DNA strands taken from different genomes with a common ancestor, we get a measure of the minimum number of point mutations that could have occurred on the evolutionary path between the two strands.
This is called the 'Hamming distance'.
It is found by comparing two DNA strands and counting how many of the nucleotides are different from their equivalent in the other string.
GAGCCTACTAACGGGAT CATCGTAATGACGGCCT ^ ^ ^ ^ ^ ^^
The Hamming distance between these two DNA strands is 7.
The Hamming distance is only defined for sequences of equal length, so an attempt to calculate it between sequences of different lengths should not work. The general handling of this situation (e.g., raising an exception vs returning a special value) may differ between languages.
For installation and learning resources, refer to the Ruby resources page.
For running the tests provided, you will need the Minitest gem. Open a terminal window and run the following command to install minitest:
gem install minitest
If you would like color output, you can
require 'minitest/pride' in
the test file, or note the alternative instruction, below, for running
the test file.
Run the tests from the exercise directory using the following command:
To include color from the command line:
ruby -r minitest/pride hamming_test.rb
The Calculating Point Mutations problem at Rosalind http://rosalind.info/problems/hamm/
It's possible to submit an incomplete solution so you can see how others have completed the exercise.
require 'minitest/autorun' require_relative 'hamming' # Common test data version: 2.1.0 b5d154b class HammingTest < Minitest::Test def test_empty_strands # skip assert_equal 0, Hamming.compute('', '') end def test_identical_strands skip assert_equal 0, Hamming.compute('A', 'A') end def test_long_identical_strands skip assert_equal 0, Hamming.compute('GGACTGA', 'GGACTGA') end def test_complete_distance_in_single_nucleotide_strands skip assert_equal 1, Hamming.compute('A', 'G') end def test_complete_distance_in_small_strands skip assert_equal 2, Hamming.compute('AG', 'CT') end def test_small_distance_in_small_strands skip assert_equal 1, Hamming.compute('AT', 'CT') end def test_small_distance skip assert_equal 1, Hamming.compute('GGACG', 'GGTCG') end def test_small_distance_in_long_strands skip assert_equal 2, Hamming.compute('ACCAGGG', 'ACTATGG') end def test_non_unique_character_in_first_strand skip assert_equal 1, Hamming.compute('AAG', 'AAA') end def test_non_unique_character_in_second_strand skip assert_equal 1, Hamming.compute('AAA', 'AAG') end def test_same_nucleotides_in_different_positions skip assert_equal 2, Hamming.compute('TAG', 'GAT') end def test_large_distance skip assert_equal 4, Hamming.compute('GATACA', 'GCATAA') end def test_large_distance_in_off_by_one_strand skip assert_equal 9, Hamming.compute('GGACGGATTCTG', 'AGGACGGATTCT') end def test_disallow_first_strand_longer skip assert_raises(ArgumentError) do Hamming.compute('AATG', 'AAA') end end def test_disallow_second_strand_longer skip assert_raises(ArgumentError) do Hamming.compute('ATA', 'AGTG') end end end
class Hamming def self.compute(strand1, strand2) raise ArgumentError unless strand1.length == strand2.length (0..strand1.length).count do |i| strand1[i] != strand2[i] end end end
A huge amount can be learnt from reading other people’s code. This is why we wanted to give exercism users the option of making their solutions public.
Here are some questions to help you reflect on this solution and learn the most from it.