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Maximum Likelihood
Estimation
Lecture – 8
Nafis Neehal, Lecturer, Department of CSE, DIU
CONTENTS
1. Maximum Likelihood Estimation
2. Calculate Maximum Likelihood of a Phylogenetic
Tree with known history
1. Maximum Likelihood Estimation
Computing Likelihood if History is Known
Maximum Likelihood Estimation Data (Given)
1. Tree Topology with Branch Lengths
(Given)
3. Substitution Rate Matrix (Given)
• Denoted by Q
• QAC means substitution rate of A to C = 0.541
(From Q Matrix)
(EXTRA)
Probability ( A -> C ) = ( QAC ) / ( QAC + QAG + QAT )
= 0.541 / ( 0.541 + 0.787 + 0.588 )
= 0.541 / 1.916
= 0.282
2. Stationary Probabilities (Given)
πa = 0.138
πc = 0.188
πg = 0.495
πt = 0.179
Maximum Likelihood Estimation Data (Example)
πA = 0.138, πC = 0.188, πG = 0.495, πT = 0.179
History (Given)
Branch Length
(Given)
=
Maximum Likelihood
Maximum Likelihood Estimation Data (Example Explained)
▹πT for Root’s Stationary Probability
▹For each branch which has same start
and end point, multiply e (branch length) x Q
(start alphabet, end alphabet)
▹For one branch (as you can see, the 3rd
branch) there is a transition in history.
Started from T, then transitioned from T
to G then finally G to G from that
transition point
▹For this kind of branch, you have to
multiply and extra (-QTT) for the T-T
transition from initial point to transition
point and another extra (-QTG/QTT) ratio
as it changing from T to G for the G-G
transition
=
Maximum Likelihood
▹ Up to T-G transition point
in 3rd branch, the T-T
branch length is 0.045
▹ Total branch length is
0.15
▹ So G-G branch length will
be (0.15-0.045) = 0.105
1 Million Years agoHuman beings left Africa
50,000 years ago
Humans navigated in the Indian
Ocean in boats
Neanderthan
You may be a part of it
Evolution
Its Still HAPPENING !!!
Final-Done

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Lecture 8

  • 1. Maximum Likelihood Estimation Lecture – 8 Nafis Neehal, Lecturer, Department of CSE, DIU
  • 2. CONTENTS 1. Maximum Likelihood Estimation 2. Calculate Maximum Likelihood of a Phylogenetic Tree with known history
  • 3. 1. Maximum Likelihood Estimation Computing Likelihood if History is Known
  • 4. Maximum Likelihood Estimation Data (Given) 1. Tree Topology with Branch Lengths (Given) 3. Substitution Rate Matrix (Given) • Denoted by Q • QAC means substitution rate of A to C = 0.541 (From Q Matrix) (EXTRA) Probability ( A -> C ) = ( QAC ) / ( QAC + QAG + QAT ) = 0.541 / ( 0.541 + 0.787 + 0.588 ) = 0.541 / 1.916 = 0.282 2. Stationary Probabilities (Given) πa = 0.138 πc = 0.188 πg = 0.495 πt = 0.179
  • 5. Maximum Likelihood Estimation Data (Example) πA = 0.138, πC = 0.188, πG = 0.495, πT = 0.179 History (Given) Branch Length (Given) = Maximum Likelihood
  • 6. Maximum Likelihood Estimation Data (Example Explained) ▹πT for Root’s Stationary Probability ▹For each branch which has same start and end point, multiply e (branch length) x Q (start alphabet, end alphabet) ▹For one branch (as you can see, the 3rd branch) there is a transition in history. Started from T, then transitioned from T to G then finally G to G from that transition point ▹For this kind of branch, you have to multiply and extra (-QTT) for the T-T transition from initial point to transition point and another extra (-QTG/QTT) ratio as it changing from T to G for the G-G transition = Maximum Likelihood ▹ Up to T-G transition point in 3rd branch, the T-T branch length is 0.045 ▹ Total branch length is 0.15 ▹ So G-G branch length will be (0.15-0.045) = 0.105
  • 7. 1 Million Years agoHuman beings left Africa 50,000 years ago Humans navigated in the Indian Ocean in boats Neanderthan You may be a part of it Evolution Its Still HAPPENING !!!