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Parsimony analysis

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Page 1: Parsimony analysis

Welcome

Page 2: Parsimony analysis

Topic

Banking

Management SystemParsimony Method for

Phylogenic Tree Analysis

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Presented By

Anika OhabID:142-15-3568

Abul HasnathID:142-15-3532

Umme HabibaID: 142-15-3677

Shahinur Rahman ID: 142-15-3606

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Introduction

kinds

terminology

construction

Parsimony method

advantage

disadvantage

Several criteria

Contents

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IntroductionA 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.

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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.

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phylogenetic tree

Rooted Unrooted

Kinds

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“Rooted” &“Unrooted” treeA 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.

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The bifurcating treeA tree that bifurcates has a maximum of 2

descendants arising from each of the interior nodes.

Diagram:

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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

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Parsimony analysisParsimony 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

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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

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Frog

Coc

odile

Bird

Kan

gero

o

Bat

Hum

an

Hairabsentpresent

Frog

Kan

gero

o

Coc

odile

Hum

an

Bat

Bird

Tree A1 step

Tree B2 steps

Character Fit

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Parsimony AnalysisGiven 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

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Frog

Bird

Crocodile

Kangeroo

Bat

Human

amni

on

hair

win

gs

anto

rbita

l fe

nest

ra

plac

enta

lact

atio

n

Tree 1

Tree 2

T A

X A

FIT

-

-

-

-

--

+

-

+

-

+

-

+

-

+

-

+

-

+

-

+

-

+

-

+

-

+

-

+ -

+

-

CHARACTERS

1 2 3 4 5 6

+

+

+

+

1

1

TREE LENGTH

1 1 1 1 2 7

2 2 2 2 1 10

Frog

Coc

odile

Kan

gero

o

Bat Bird

Hum

an

1

23

6

44

5

52

3

Tree 2

Coc

odile

Kan

gero

o

Frog

Bird Bat Hum

an

1

Tree 1

23

4

66

5

Of these two trees, Tree 1 has the shortest length and is the most parsimoniousBoth trees require some homoplasy (extra steps)

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Results of parsimony analysisOne 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

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Tree-building methods can be assessed on the basis of several criteria:

Efficiency Power

consistency

robustness

falsifiability

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Parsimony - advantagesIt’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 aresmall

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Parsimony - disadvantagesmay lead to the delusion that you know

exactly whathappened 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 noassumptions

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The End

Thank You