Today, I continued learning about the major methods for estimating phylogenetic trees. The Neighbor Joining Method is one of the most popular distance algorithmic method. It produces a "single, strictly bifurcating tree," which means that each internal node has exactly two branched descending from it. I downloaded another file of data for practice to construct the tree.
First I opened up the file LargeData.meg from MEGA. The window shows DNA sequence alignment.
Next, I had to determine whether the data was even suitable for estimating a Neighbor Joining Tree. In the book, it said that if the average pairwise Jukes-Cantor Distance is more than 1.0, the data isn't suitable for making NJ trees and another phylogenetic method should be used. To find the Jukes-Cantor distance, I computed the overall mean of the distances, and found the average distance to be 0.534, which is suitable for making NJ trees.
I constructed the tree by choosing Construct/Test Neighbor Joining Tree from Phylogeny menu. After using the "bootstrapping" method to test the reliability of the tree, and making sure that the tree was being constructed using the Neighbor Joining Method, I produced the following tree using the program:
I constructed the tree by choosing Construct/Test Neighbor Joining Tree from Phylogeny menu. After using the "bootstrapping" method to test the reliability of the tree, and making sure that the tree was being constructed using the Neighbor Joining Method, I produced the following tree using the program:
There are many different ways to represent the same data in a tree. I played around with some of the various options and also got this circular tree:
Yay, a tree! Now you are really making progress!!
ReplyDeleteI am impressed with your use of systematics language in your posts. You are clearly understanding the process, and here you demonstrate that you can produce. This bodes well for the future of your project!