[SOLVED] QBIO401-Assignment 5

Description

We are going to write a UPGMA algorithm in Python and analyze some human data.

On Blackboard, you can find a file named upgmaData.py, which contains:

1. humansList (and testList) are species lists. They are in the form of a tuple.
2. humansDistances (and testDistances) are dictionaries specifying pairwise distances between species. They are in the form where the key is a tuple which is a pair of species name, e.g., (“species A”,”species B”) and the value is the pairwise distance. The following are the details for the human data:

Modern human data: distances based on mitochondrial sequence

Note: use “from upgmaData import *” on the first line of your code to be able to use the data.

Write the following Python class for a tree node (as taught in Jinsen’s discussion):

1.      TreeNode Has four properties including key, distance, left and right, where key is for storing species name, distance is for branch length, left is for the left child and right is for the right child. The class has a function print to print the tree structure in the form of (key, distance, left, right). For example, (‘W_X’,0.5,(‘W’,0,(),()),(‘X’,0,(),())) is for the tree W_X with left child (‘W’,0,(),()) and right child (‘X’,0,(),()); the branch length to its child is 0.5.

Write the following functions:

2.      findClosestPair(Distances) Inputs Distances dictionary and returns the key for the pair of nodes that are closest. For example, if the input is testDistances, the function returns (‘W’, ‘X’).

3.      updateDist(Distances, newNode)

Inputs Distances dictionary and a new tree node. Updates the Distances dictionary by adding the distances between newNode and all the other nodes. Does not calculate the distance between newNode and its children in the Distances. This function returns the updated Distances dictionary.

4.      upgma(Distances)

This function runs the UPGMA algorithm described in lecture. First, it initializes a list TreeNodesList with multiple new TreeNode referring to humansList (the list TreeNodesList should contain six TreeNodes). Then, it repeats the following steps until there is only one tree node left in the list TreeNodesList, at which point this tree is returned.

1. Find the key for the closest pair of nodes in Distances (use findClosestPair)
2. Create a new TreeNode and assign the pair of nodes stored in TreeNodesList as its children. Calculate the distance between the new TreeNode to its children and store the value in the new TreeNode.
3. Update the TreeNodesList by removing the pair of nodes referring to a.
4. Update the Distances dictionary (use updateDist)
5. Add the new TreeNode into TreeNodesList.