This document provides an introduction to parsimony methods for phylogenetic tree analysis. It begins by defining phylogenetic trees and their use in representing evolutionary relationships. It then describes the basic structure of rooted vs unrooted trees and bifurcating trees. The document introduces parsimony analysis, which works by determining the best fit of character data to potential tree models and finding the most parsimonious trees that minimize evolutionary changes. It concludes by discussing some advantages of parsimony methods in being simple and having good statistical properties, as well as some disadvantages like underestimating branch lengths and having an implicit evolutionary model.

1. Welcome

2. Topic
Parsimony Method for
Phylogenic Tree
Analysis

3. Presented By
Anika Ohab
ID:142-15-3568
Abul Hasnath
ID:142-15-3532
Umme Habiba
ID: 142-15-3677
Shahinur Rahman
ID: 142-15-3606

4. Introduction
kinds
terminology
construction
Parsimony method
advantage
disadvantage
Several criteria
Contents

5. Introduction
 A phylogenetic tree or evolutionary tree is
a branching diagram or "tree’’showing the
inferred evolutionary relationships among
various biological species
or
other entities—their phylogeny—based
upon similarities and differences in their
physical or genetic characteristics.
 Phylogenetic trees are central to the field
of phylogenetics.

6. What does this tree look like?
 There are many different ways to represent the
information found in a phylogenetic tree.
 The basic format of a tree is generally in one of the
two forms shown, although there are other ways to
represent the data.

8. phylogenetic tree
Rooted Unrooted
Kinds

9. “Rooted” &“Unrooted” tree
 A rooted tree is used to make inferences about
the most common ancestor of the leaves or
branches of the tree. Most commonly the root is
referred to as an “outgroup”.
 An unrooted tree is used to make an illustration
about the leaves or branches, but not make
assumption regarding a common ancestor.

11. The bifurcating tree
 A tree that bifurcates has a maximum of 2
descendants arising from each of the
interior nodes.
Diagram:

13. C
o
n
s
t
r
u
c
t
I
o
n
Computational
Phylogenetics Methods
Distance-matrix Methods
Neighbor-joining or
UPGMA
maximum likelihood
Parsimony Methods

14. Parsimony analysis
 Parsimony methods provide one way of choosing
among alternative phylogenetic hypotheses
 The parsimony criterion favours hypotheses that
maximise congruence and minimise homoplasy
 It depends on the idea of the fit of a character to a
tree

15. Character Fit
 Initially, we can define the fit of a character to a
tree as the minimum number of steps required to
explain the observed distribution of character
states among taxa
 This is determined by parsimonious character
optimization
 Characters differ in their fit to different trees

16. Frog
Cocodile
Bird
Kangeroo
Bat
Human
Hair
absent
present
Frog
Kangeroo
Cocodile
Human
Bat
Bird
Tree A
1 step
Tree B
2 steps
Character Fit

17. Parsimony Analysis
 Given a set of characters, such as aligned sequences
 parsimony analysis works by determining the fit
(number of steps) of each character on a given tree
 Most parsimonious trees (MPTs) have the minimum
tree length needed to explain the observed
distributions of all the characters

18. Frog
Bird
Crocodile
Kangeroo
Bat
Human
amnion
hair
wings
antorbital
fenestra
placenta
lactation
Tree 1
Tree 2
TAXAFIT
-
-
-
-
--
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+ -
+
-
CHARACTERS
1 2 3 4 5 6
+
+
+
+
1
1
TREE
LENGTH
1 1 1 1 2 7
2 2 2 2 1 10
Frog
Cocodile
Kangeroo
Bat
Bird
Human
1
2
3
6
4
4
5
5
2
3
Tree 2
Cocodile
Kangeroo
Frog
Bird
Bat
Human
1
Tree 1
2
3
4
66
5
Of these two trees, Tree 1 has the shortest length and is the most
parsimonious
Both trees require some homoplasy (extra steps)

19. Results of parsimony analysis
 One or more most parsimonious trees
 Hypotheses of character evolution associated with each
tree lengths
 Various tree and character statistics describing the fit
between tree and data
 Suboptimal trees - optional

20. Tree-building methods can be assessed on
the basis of several criteria:
Efficiency Power
consistency robustness
falsifiability

21. Parsimony - advantages
 It’s a simple method - easily understood operation
 Its does not seem to depend on an explicit model of
evolution
 gives both trees and associated hypotheses of
character evolution
 good statistical properties when amounts of change are
small

22. Parsimony - disadvantages
 may lead to the delusion that you know exactly what
happened in evolution, in detail.
Underestimates branch lengths
 Model of evolution is implicit - behaviour of method
not well understood
 not model-based so people think it makes no
assumptions

23. The End
Thank You