6 Dot Plot

6 Dot Plot - 1 Introduction to Bioinformatics Elements of...

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1 Introduction to Bioinformatics/ Elements of Bioinformatics Pairwise sequence alignment – Dot Plot
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2 References Mount D.W. (2004) Bioinformatics: Sequence and Genome Analysis. 2 nd ed. Cold Spring Harbor Lab. Press, N.Y. Chapter 3. Baxevanis, A.D., and Ouellette, B.F.F. (2005) Bioinformatics - A practical guide to the analysis of genes and proteins (3rd ed). John Wiley and Sons, NY. Chapter 11. • Altschul S.F., and Gish W. (1996) Local alignment statistics. Methods in Enzymology 266: 460-480.
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3 Sequence alignment Seq a GGCCTCCTC |||| || | Seq b GGCC-CCAC An alignment GGCCTCCAC GGCCTCCT C GGCC- CCAC A T One possible evolutionary history T Seq a Seq b
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4 Types of alignment Pairwise alignment Multiple alignment G KGN A S K QQVQLMVSK G KGH A S K RQVQVMVSK G YGN A D K SEVQEAVAR G IGS A E K SQVQHMVRT G TGG A D K QQVQMMVMH G YGH A G K EQILYMIKH G SGR A D K AQVGAMVTR G NAK A N K AEVAAMVQN GKG N ASK Q QVQ L MVSK ||| ||| ||| |||| GKG H ASK R QVQ V MVSK
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5 Types of alignment Global alignment: align the entire sequence Local alignment: align the region with the highest density of match Sequence A Sequence B
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6 Why align? • Sequence alignment is fundamental to sequence analysis: – infer common ancestry – phylogenetic studies – reveal conserved domains – database search
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7 How to align? • Pairwise alignment – Dot plot method: graphical method to visualize regions of similarity – Dynamic programming method: optimal alignment • Multiple alignment – Progressive alignment method
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8 Dot Plot • Columns correspond to residues in the first sequence. • Rows correspond to residues in the second sequence. • A dot is placed whenever residue from the first sequence match the residue from the second sequence. • Visually inspect the matrix for regions of similarities between the two sequences.
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9 Dot Plot 10 5 1 T A C A C T G A T A G G 1 C T A G 5 T C A G A 10 T SeqA 5’GCTAGTCAGAT SeqB 5’GATAGTCACAT SeqA SeqB
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10 Dot Plot Identical pair = match SeqA 5’GCTAGTCAGAT SeqB 5’GATAGTCACAT 10 5 1 T A C A C T G A T A G G 1 C T A G 5 T C A G A 10 T SeqA SeqB
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11 Dot plot with wordsearch • Looks for regions where words of a specified length (k-tuple) have an exact match in both sequences. • A longer word size displays less random noise, but may miss regions of lower degree of similarity (less sensitive). • More suitable for closely related sequences. • Form the basis of rapid sequence database search methods e.g. FASTA, Fast stage of ClustalW
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12 TT TG TC TA GT GG GC GA CT CG CC CA AT AG AC AA Position (Sequence B) Position (sequence A) Words Dot plot with wordsearch wordsize = 2: Seq A 5’GCTAGTCAGAT Seq B 5’GATAGTCACAT
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13 TT TG TC TA GT GG 1 GC GA CT CG CC CA AT AG AC AA Position (Sequence B) Position (sequence A) Words Dot plot with wordsearch wordsize = 2: Seq A 5’ GC TAGTCAGAT Seq B 5’GATAGTCACAT
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14 TT TG TC TA GT GG 1 GC GA 2 CT CG CC CA AT AG AC AA Position (Sequence B) Position (sequence A) Words Dot plot with wordsearch wordsize = 2: Seq A 5’G CT AGTCAGAT Seq B 5’GATAGTCACAT
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This note was uploaded on 07/29/2010 for the course BIOC BIOC1805 taught by Professor Dr.brianwong during the Summer '09 term at HKU.

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6 Dot Plot - 1 Introduction to Bioinformatics Elements of...

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