Ch06_Alignment

Ch06_Alignment - An Introduction to Bioinformatics...

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    www.bioalgorithms.info An Introduction to Bioinformatics Algorithms Sequence Alignment
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Outline Global Alignment Scoring Matrices Local Alignment Alignment with Affine Gap Penalties
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Outline - CHANGES Scoring Matrices - ADD an extra slidewith an example of 5x5 matrix. Local Alignment – ADD extra slide showing a naïve approach to local alignment
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info From LCS to Alignment: Change up the Scoring The Longest Common Subsequence (LCS) problem —the simplest form of sequence alignment – allows only insertions and deletions (no mismatches). In the LCS Problem, we scored 1 for matches and 0 for indels Consider penalizing indels and mismatches with negative scores Simplest scoring schema : +1 : match premium : mismatch penalty : indel penalty
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Simple Scoring When mismatches are penalized by –μ , indels are penalized by –σ , and matches are rewarded with +1 , the resulting score is: #matches – μ ( #mismatches) – σ ( #indels)
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info The Global Alignment Problem Find the best alignment between two strings under a given scoring schema Input : Strings v and w and a scoring schema Output : Alignment of maximum score ↑→ = - б = 1 if match = - µ if mismatch s i-1,j-1 +1 if v i = w j s i,j = max s i-1,j-1 if v i ≠ w j s i-1,j - σ s i,j-1 - σ μ : mismatch penalty σ : indel penalty
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Scoring Matrices To generalize scoring, consider a (4+1) x(4+1) scoring matrix δ. In the case of an amino acid sequence alignment, the scoring matrix would be a (20+1)x(20+1) size. The addition of 1 is to include the score for comparison of a gap character “-”. This will simplify the algorithm as follows: s i-1,j-1 + δ (v i , w j ) s i,j = max s i-1,j + δ (v i , -) s i,j-1 + δ (-, w j )
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Measuring Similarity Measuring the extent of similarity between two sequences Based on percent sequence identity Based on conservation
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Percent Sequence Identity The extent to which two nucleotide or amino acid sequences are invariant A C  C  T G  A  G  –  A G  A C  G  T G  –  G  C  A G 70% identical mismatch indel
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An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Making a Scoring Matrix Scoring matrices are created based on biological evidence. Alignments can be thought of as two
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This note was uploaded on 12/03/2011 for the course BIO 118 taught by Professor Staff during the Fall '08 term at Rutgers.

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Ch06_Alignment - An Introduction to Bioinformatics...

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