Tècniques i Eines Bioinformàtiques

•Bioinformatics, Sequence and Genome Analysis

David W. Mount

•Flexible Pattern Matching in Strings (2002)

Gonzalo Navarro and Mathieu Raffinot

•Algorithms on strings (2001)

M. Crochemore, C. Hancart and T. Lecroq

•http://www-igm.univ-mlv.fr/~lecroq/string/index.html

Algorismes i estructures eficients de cerca

String matching: definition of the problem (text,pattern)

depends on what we have: text or patterns• Exact matching:

• 1 pattern ---> The algorithm depends on |p| and ||

• k patterns ---> The algorithm depends on k, |p| and ||

• The text ----> Data structure for the text (suffix tree, ...)

• The patterns ---> Data structures for the patterns

• Approximate matching: • Dynamic programming • Sequence alignment (pairwise and multiple)

Approximate string matching

For instance, given the sequence

CTACTACTACGTGACTAATACTGATCGTAGCTAC…

search for the pattern ACTGA allowing one error…

… but what is the meaning of “one error”?

Edit distance

We accept three types of errors:

The edit distance d between two strings is the minimum number of

substitutions,insertions and deletionsneeded to transform the first string into the second one

d(ACT,ACT)= d(ACT,AC)= d(ACT,C)=d(ACT,)= d(AC,ATC)= d(ACTTG,ATCTG)=

3. Deletion: ACCGTGAT ACCGGAT

2. Insertion: ACCGTGAT ACCGATGAT

1. Mismatch: ACCGTGAT ACCGAGAT

Indel

Edit distance

We accept three types of errors:

The edit distance d between two strings is the minimum number of

substitutions,insertions and deletionsneeded to transform the first string into the second one

3. Deletion: ACCGTGAT ACCGGAT

2. Insertion: ACCGTGAT ACCGATGAT

1. Mismatch: ACCGTGAT ACCGAGAT

d(ACT,ACT)= d(ACT,AC)= d(ACT,C)=d(ACT,)= d(AC,ATC)= d(ACTTG,ATCTG)=

Indel

0 1 23 1 2

Edit distance and alignment of strings

• ACT and ACT : ACT ACT

• ACTTG and ATCTG:

• ACT and AT: ACT A -T

ACTTG ATCTG

ACT - TGA - TCTG

Given d(ACT,ACT)=0 d(ACT,AC)=1 d(ACTTG,ATCTG)=2which is the best alignment in every case?

The Edit distance is related with the best alignment of strings

Then, the alignment suggest the substitutions, insertions and deletions to transform one string into the other

Edit distance and alignment of strings

But which is the distance between the strings

ACGCTATGCTATACG and ACGGTAGTGACGC?

… and the best alignment between them?

1966 was the first time this problem was discussed…

and the algorithm was proposed in 1968,1970,…

using the technique called “Dynamic programming”

Edit distance and alignment of strings

C T A C T A C T A C G T

ACTGA

Edit distance and alignment of strings

C T A C T A C T A C G T

ACTGA

Edit distance and alignment of strings

C T A C T A C T A C G T ACTGA

The cell contains the distance between AC and CTACT.

Edit distance and alignment of strings

C T A C T A C T A C G T A C T GA

?

Edit distance and alignment of strings

C T A C T A C T A C G T 0 A C T GA

?

Edit distance and alignment of strings

C T A C T A C T A C G T 0 1 A C T GA

-C

?

Edit distance and alignment of strings

C T A C T A C T A C G T 0 1 2 A C T GA

- -CT

?

Edit distance and alignment of strings

C T A C T A C T A C G T 0 1 2 3 4 5 6 7 8 …A C T GA

- - - - - -CTACTA

Edit distance and alignment of strings

C T A C T A C T A C G T 0 1 2 3 4 5 6 7 8 …A ?C ?T ?GA

Edit distance and alignment of strings

C T A C T A C T A C G T 0 1 2 3 4 5 6 7 8 …A 1C 2T 3G…A

ACT - - -

C T A C T A C T A C G T 0 1 2 3 4 5 6 7 8 …A 1C 2T 3GA

C T A C T A C T A C G T A C TGA

Edit distance and alignment of strings

BA(AC,CTA) -C

BA(A,CTA)CC

BA(A,CTAC)C -

BA(AC,CTAC)= best

d(AC,CTAC)=min

d(AC,CTA)+1

d(A,CTA)

d(A,CTAC)+1

Edit distance and alignment of strings

Connect to

http://alggen.lsi.upc.es/docencia/ember/leed/Tfc1.htm

and use the global method.

Edit distance and alignment of strings

How this algorithm can be applied

to the approximate search?

to the K-approximate string searching?

K-approximate string searching

C T A C T A C T A C G T A C T G G T G A A …

ACTGA

This cell …

K-approximate string searching

C T A C T A C T A C G T A C T G G T G A A …

ACTGA

This cell gives the distance between (ACTGA, CT…GTA)…

…but we only are interested in the last characters

K-approximate string searching

C T A C T A C T A C G T A C T G G T G A A …

ACTGA

This cell gives the distance between (ACTGA, CT…GTA)…

…but we only are interested in the last characters

K-approximate string searching

* * * * * * C T A C G T A C T G G T G A A …

ACTGA

This cell gives the distance between (ACTGA, CT…GTA)…

…but we only are interested in the last characters…

…no matter where they appears in the text, then…

K-approximate string searching

* * * * * * C T A C G T A C T G G T G A A … 0ACTGA

This cell gives the distance between (ACTGA, CT…GTA)…

…but we only are interested in the last characters…

…no matter where they appears in the text, then…

K-approximate string searching

* * * * * * C T A C G T A C T G G T G A A … 0ACTGA

This cell gives the distance between (ACTGA, CT…GTA)…

…but we only are interested in the last characters…

…no matter where they appears in the text, then…

K-approximate string searching

C T A C T A C T A C G T A C T G G T G A A … 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0ACTGA

This cell gives the distance between (ACTGA, CT…GTA)…

…but we only are interested in the last characters…

…no matter where they appears in the text, then

K-approximate string searching

Connect to

http://alggen.lsi.upc.es/docencia/ember/leed/Tfc1.htm

and use the semi-global method.

Bioinformatics

Pairwise and multiple alignment

Pairwise alignment

Edit distance:

match=0 mismatch=1 indel=1

d(A,CTAC)+1d(AC,CTACT)=minimum d(A,CTA)….+1 d(AC,CTA)+1

Similarity:

match=1 mismatch=-1 indel=-2

s(A,CTAC)-2s(AC,CTACT)=maximum s(A,CTA) 1 s(AC,CTA)-2

-+

Pairwise alignment

Connect to

http://alggen.lsi.upc.es

Links to TEACHING EMBER LePA

A

C

A

-1__

Pairwise to multiple alignment

What happens with three strings?

Let n be their lenght, then the cost becomes

S3

S2

S1

O(n3) “O(23)” “O(32)”

And with k strings? O(nk 2k k2)

Multiple alignment

Programs of multialignment use different heuristics:

Clustal (Progressive alignment)

http://www.ebi.ac.uk/clustalw

TCoffee (Progressive alignment + data bases)

http://igs-server.cnrs-mrs.fr/Tcoffee_cgi/index.cgi

HMM (Hidden Markov Models)

Multiple alignment

Connect to

http://alggen.lsi.upc.es/

and follow the links TEACHING EMBER.