an introduction to multiple alignments · institut suisse de bioinformatique cn+lf-2003.10 what do...

Swiss Institute of BioinformaticsInstitut Suisse de Bioinformatique

CN+LF-2003.10

An introduction to multiple alignments

© Cédric Notredame


CN+LF-2003.10

Overview

Multiple alignmentsHow-to, Goal, problems, use

PatternsPROSITE database, syntax, use

PSI-BLASTBLAST, matrices, use

[ Profiles/HMMs ] …


CN+LF-2003.10

Overview

What are multiple alignments?How can I use my alignments?How does the computer align the sequences?

The progressive alignment algorithmWhat are the difficulties?Pre-requisite?

How can we compare sequences?How can we align sequences?


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Sometimes two sequences are not enough

The man with TWO watches NEVER knows the exact time


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What is a multiple sequence alignment?

What can it do for me?How can I produce one of these?How can I use it?

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKDwheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSEtrybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGPmouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP

***. ::: .: .. . : . . * . *: *

chite AATAKQNYIRALQEYERNGG-wheat ANKLKGEYNKAIAAYNKGESAtrybr AEKDKERYKREM---------mouse AKDDRIRYDNEMKSWEEQMAE

* : .* . :


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What is a multiple sequence alignment?

Structural/biochemical criteriaResidues playing a similar role end up in the same column.

Evolution criteriaResidues having the same ancestor end up in the same column.


***. ::: .: .. . : . . * . *: *


* : .* . :


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How can I use a multiple alignment?chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKDwheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSEtrybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGPunknown -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP

***. ::: .: .. . : . . * . *: *

chite AATAKQNYIRALQEYERNGG-wheat ANKLKGEYNKAIAAYNKGESAtrybr AEKDKERYKREM---------unknown AKDDRIRYDNEMKSWEEQMAE

* : .* . :

Extrapolation

SwissProt

Unkown Sequence

Homology?

Less Than 30 % idBUT

Conserved where it MATTERS


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How can I use a multiple alignment?chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKDwheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSEtrybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGPmouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP

***. ::: .: .. . : . . * . *: *


* : .* . :

Extrapolation

Prosite Patterns

P-K-R-[PA]-x(1)-[ST]…


CN+LF-2003.10

How can I use a multiple alignment?

Extrapolation

Prosite Patterns

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKDwheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSEtrybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGPmouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-IQGKLKLVNEAWKNLSP

***. ::: .: .. . : . . * . *: *


* : .* . :

L?K>R

Prosite Profiles -More Sensitive-More Specific

AFDEFGHQIVLW


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PROSITE profile (see also HMMs)

A Substitution Cost For Every Amino Acid, At Every Position


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Phylogeny


***. ::: .: .. . : . . * . *: *


* : .* . :

chite

wheat

trybr

mouse

-Evolution-Paralogy/Orthology


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Phylogeny


***. ::: .: .. . : . . * . *: *


* : .* . :

Struc. Prediction

Column Constraint

Evolution Constraint

Structure Constraint


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Phylogeny


***. ::: .: .. . : . . * . *: *


* : .* . :

Struc. Prediction

PsiPred or PhDFor secondary Structure Prediction: 75% Accurate.Threading: is improving but is not yet as good.


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Phylogeny

Struc. Prediction


***. ::: .: .. . : . . * . *: *


* : .* . :

Caution!

Automatic MultipleSequence Alignment methodsare not always perfect…


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The problem

why is it difficult to compute a multiple sequence alignment?


***. ::: .: .. . : . . * . *: *

Computation

What is the good alignment?

Biology

What is a good alignment?


CN+LF-2003.10

The problem

why is it difficult to compute a multiple sequence alignment?

CIRCULAR PROBLEM....

GoodSequences

GoodAlignment


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The problem

Same as pairwise alignment problemWe do NOT know how sequences evolve.We do NOT understand the relation between structures and sequences.

We would NOT recognize the “correct” alignment if we had it IN FRONT of our eyes…


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The Charlie Chaplin paradox


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What do I need to know to make a good multiple alignment?

How do sequences evolve?How does the computer align the sequences?How can I choose my sequences?What is the best program?How can I use my alignment?


CN+LF-2003.10

An alignment is a story

ADKPKRPLSAYMLWLN

ADKPKRPLSAYMLWLN ADKPKRPLSAYMLWLN

ADKPRRPLS-YMLWLN ADKPKRPKPRLSAYMLWLN

Mutations+

Selection

ADKPRRP---LS-YMLWLNADKPKRPKPRLSAYMLWLN

InsertionDeletion

Mutation


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Homology

Same sequences -> same origin? -> same function? -> same 3D fold?

Length

%Sequence Identity

30%

100

Same 3D Fold

Twilight Zone


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Convergent evolution

AFGP with (ThrAlaAla)nSimilar To Trypsinogen

AFGP with (ThrAlaAla)nNOT

Similar to Trypsinogen

N

S

Chen et al, 97, PNAS, 94, 3811-16


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Residues and mutations

All residues are equal, but some more than others…

PG

SC

LI

T

V A

WYF QH

K

R

ED N

Aliphatic

Aromatic

Hydrophobic

Polar

SmallM

Accurate matrices are data driven rather than knowledge driven

GC


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Substitution matrices

Different Flavors:

• Pam: 250, 350• Blosum: 45, 62• …


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What is the best substition matrix?

Mutation rates depend on families

Choosing the right matrix may be trickyGonnet250 > BLOSUM62 > PAM250 Depends on the family, the program used and its tuning

Family S N Histone3 6.4 0Insulin 4.0 0.1Interleukin I 4.6 1.4α−Globin 5.1 0.6Apolipoprot. AI 4.5 1.6Interferon G 8.6 2.8

Rates in Substitutions/site/Billion Years as measured on Mouse Vs Human (0.08 Billion years)


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Insertions and deletions?

Indel Cost

L

Cost

L

Cost

L

Affine Gap PenaltyCost=GOP+GEP*L


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How to align many sequences?

Exact algorithms are computing time consumingNeedlemann & Wunsch Smith & Waterman

2 Globins =>1 sec


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3 Globins =>2 mn




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4 Globins =>5 hours



-> heuristic wished


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5 Globins =>3 weeks



-> heuristic really wished!


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6 Globins =>9 years



-> heuristic required!


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-> heuristic definitely required!

7 Globins =>1000 years


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8 Globins =>150 000 years



-> heuristic please!…


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Existing methods1-Carillo and Lipman:

-MSA, DCA.

-Few Small Closely Related Sequence.

2-Segment Based:

-DIALIGN, MACAW.

-May Align Too Few Residues

-Do Well When They Can Run.

3-Iterative:-HMMs, HMMER, SAM.

-Slow, Sometimes Inacurate

-Good Profile Generators

4-Progressive:

-ClustalW, Pileup, Multalign…

-Fast and Sensitive


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Progressive alignmentFeng and Dolittle, 1980; Taylor 1981

Dynamic Programming Using A Substitution Matrix


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Progressive alignmentFeng and Dolittle, 1980; Taylor 1981

-Depends on the ORDER of the sequences (Tree).

-Depends on the CHOICE of the sequences.

-Depends on the PARAMETERS:

•Substitution Matrix.

•Penalties (Gop, Gep).

•Sequence Weight.

•Tree making Algorithm.


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Progressive alignment

Works well when phylogeny is denseNo outlayer sequenceExample: river crossing


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Selecting sequences from a BLAST output


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A common mistake

Sequences too closely related

Identical sequences brings no informationMultiple sequence alignments thrive on diversity

PRVA_MACFU SMTDLLNAEDIKKAVGAFSAIDSFDHKKFFQMVGLKKKSADDVKKVFHILDKDKSGFIEEPRVA_HUMAN SMTDLLNAEDIKKAVGAFSATDSFDHKKFFQMVGLKKKSADDVKKVFHMLDKDKSGFIEEPRVA_GERSP SMTDLLSAEDIKKAIGAFAAADSFDHKKFFQMVGLKKKTPDDVKKVFHILDKDKSGFIEEPRVA_MOUSE SMTDVLSAEDIKKAIGAFAAADSFDHKKFFQMVGLKKKNPDEVKKVFHILDKDKSGFIEEPRVA_RAT SMTDLLSAEDIKKAIGAFTAADSFDHKKFFQMVGLKKKSADDVKKVFHILDKDKSGFIEEPRVA_RABIT AMTELLNAEDIKKAIGAFAAAESFDHKKFFQMVGLKKKSTEDVKKVFHILDKDKSGFIEE

:**::*.*******:***:* :****************..::******:***********

PRVA_MACFU DELGFILKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAESPRVA_HUMAN DELGFILKGFSPDARDLSAKETKMLMAAGDKDGDGKIGVDEFSTLVAESPRVA_GERSP DELGFILKGFSSDARDLSAKETKTLLAAGDKDGDGKIGVEEFSTLVSESPRVA_MOUSE DELGSILKGFSSDARDLSAKETKTLLAAGDKDGDGKIGVEEFSTLVAESPRVA_RAT DELGSILKGFSSDARDLSAKETKTLMAAGDKDGDGKIGVEEFSTLVAESPRVA_RABIT EELGFILKGFSPDARDLSVKETKTLMAAGDKDGDGKIGADEFSTLVSES

:*** ******.******.**** *:************.:******:**


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Respect information!PRVA_MACFU ------------------------------------------SMTDLLN----AEDIKKAPRVA_HUMAN ------------------------------------------SMTDLLN----AEDIKKAPRVA_GERSP ------------------------------------------SMTDLLS----AEDIKKAPRVA_MOUSE ------------------------------------------SMTDVLS----AEDIKKAPRVA_RAT ------------------------------------------SMTDLLS----AEDIKKAPRVA_RABIT ------------------------------------------AMTELLN----AEDIKKATPCC_MOUSE MDDIYKAAVEQLTEEQKNEFKAAFDIFVLGAEDGCISTKELGKVMRMLGQNPTPEELQEM

: :*. .*::::

PRVA_MACFU VGAFSAIDS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGFIPRVA_HUMAN VGAFSATDS--FDHKKFFQMVG------LKKKSADDVKKVFHMLDKDKSGFIEEDELGFIPRVA_GERSP IGAFAAADS--FDHKKFFQMVG------LKKKTPDDVKKVFHILDKDKSGFIEEDELGFIPRVA_MOUSE IGAFAAADS--FDHKKFFQMVG------LKKKNPDEVKKVFHILDKDKSGFIEEDELGSIPRVA_RAT IGAFTAADS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGSIPRVA_RABIT IGAFAAAES--FDHKKFFQMVG------LKKKSTEDVKKVFHILDKDKSGFIEEEELGFITPCC_MOUSE IDEVDEDGSGTVDFDEFLVMMVRCMKDDSKGKSEEELSDLFRMFDKNADGYIDLDELKMM

:. . * .*..:*: *: * *. :::..:*:::**: .*:*: :** :

PRVA_MACFU LKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAES-PRVA_HUMAN LKGFSPDARDLSAKETKMLMAAGDKDGDGKIGVDEFSTLVAES-PRVA_GERSP LKGFSSDARDLSAKETKTLLAAGDKDGDGKIGVEEFSTLVSES-PRVA_MOUSE LKGFSSDARDLSAKETKTLLAAGDKDGDGKIGVEEFSTLVAES-PRVA_RAT LKGFSSDARDLSAKETKTLMAAGDKDGDGKIGVEEFSTLVAES-PRVA_RABIT LKGFSPDARDLSVKETKTLMAAGDKDGDGKIGADEFSTLVSES-TPCC_MOUSE LQ---ATGETITEDDIEELMKDGDKNNDGRIDYDEFLEFMKGVE

*: . .. :: .: : *: ***:.**:*. :** ::

-This alignment is not informative about the relation between TPCC MOUSE and the rest of the sequences.

-A better spread of the sequences is needed


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Selecting diverse sequences

PRVB_CYPCA -AFAGVLNDADIAAALEACKAADSFNHKAFFAKVGLTSKSADDVKKAFAIIDQDKSGFIEPRVB_BOACO -AFAGILSDADIAAGLQSCQAADSFSCKTFFAKSGLHSKSKDQLTKVFGVIDRDKSGYIEPRV1_SALSA MACAHLCKEADIKTALEACKAADTFSFKTFFHTIGFASKSADDVKKAFKVIDQDASGFIEPRVB_LATCH -AVAKLLAAADVTAALEGCKADDSFNHKVFFQKTGLAKKSNEELEAIFKILDQDKSGFIEPRVB_RANES -SITDIVSEKDIDAALESVKAAGSFNYKIFFQKVGLAGKSAADAKKVFEILDRDKSGFIEPRVA_MACFU -SMTDLLNAEDIKKAVGAFSAIDSFDHKKFFQMVGLKKKSADDVKKVFHILDKDKSGFIEPRVA_ESOLU --AKDLLKADDIKKALDAVKAEGSFNHKKFFALVGLKAMSANDVKKVFKAIDADASGFIE

: *: .: . .* .:*. * ** *: * : * :* * **:**PRVB_CYPCA EDELKLFLQNFKADARALTDGETKTFLKAGDSDGDGKIGVDEFTALVKA-PRVB_BOACO EDELKKFLQNFDGKARDLTDKETAEFLKEGDTDGDGKIGVEEFVVLVTKGPRV1_SALSA VEELKLFLQNFCPKARELTDAETKAFLKAGDADGDGMIGIDEFAVLVKQ-PRVB_LATCH DEELELFLQNFSAGARTLTKTETETFLKAGDSDGDGKIGVDEFQKLVKA-PRVB_RANES QDELGLFLQNFRASARVLSDAETSAFLKAGDSDGDGKIGVEEFQALVKA-PRVA_MACFU EDELGFILKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAESPRVA_ESOLU EEELKFVLKSFAADGRDLTDAETKAFLKAADKDGDGKIGIDEFETLVHEA

:** .*:.* .* *: ** :: .* **** **::** **

-A REASONABLE model now exists.

-Going further:remote homologues.


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Aligning remote homologuesPRVA_MACFU ------------------------------------------SMTDLLNA----EDIKKAPRVA_ESOLU -------------------------------------------AKDLLKA----DDIKKAPRVB_CYPCA ------------------------------------------AFAGVLND----ADIAAAPRVB_BOACO ------------------------------------------AFAGILSD----ADIAAGPRV1_SALSA -----------------------------------------MACAHLCKE----ADIKTAPRVB_LATCH ------------------------------------------AVAKLLAA----ADVTAAPRVB_RANES ------------------------------------------SITDIVSE----KDIDAATPCS_RABIT -TDQQAEARSYLSEEMIAEFKAAFDMFDADGG-GDISVKELGTVMRMLGQTPTKEELDAITPCS_PIG -TDQQAEARSYLSEEMIAEFKAAFDMFDADGG-GDISVKELGTVMRMLGQTPTKEELDAITPCC_MOUSE MDDIYKAAVEQLTEEQKNEFKAAFDIFVLGAEDGCISTKELGKVMRMLGQNPTPEELQEM

: ::

PRVA_MACFU VGAFSAIDS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGFIPRVA_ESOLU LDAVKAEGS--FNHKKFFALVG------LKAMSANDVKKVFKAIDADASGFIEEEELKFVPRVB_CYPCA LEACKAADS--FNHKAFFAKVG------LTSKSADDVKKAFAIIDQDKSGFIEEDELKLFPRVB_BOACO LQSCQAADS--FSCKTFFAKSG------LHSKSKDQLTKVFGVIDRDKSGYIEEDELKKFPRV1_SALSA LEACKAADT--FSFKTFFHTIG------FASKSADDVKKAFKVIDQDASGFIEVEELKLFPRVB_LATCH LEGCKADDS--FNHKVFFQKTG------LAKKSNEELEAIFKILDQDKSGFIEDEELELFPRVB_RANES LESVKAAGS--FNYKIFFQKVG------LAGKSAADAKKVFEILDRDKSGFIEQDELGLFTPCS_RABIT IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNADGYIDAEELAEITPCS_PIG IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNMDGYIDAEELAEITPCC_MOUSE IDEVDEDGSGTVDFDEFLVMMVRCMKDDSKGKSEEELSDLFRMFDKNADGYIDLDELKMM

: . .: .. . *: * : * :* : .*:*: :** .

PRVA_MACFU LKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAES-PRVA_ESOLU LKSFAADGRDLTDAETKAFLKAADKDGDGKIGIDEFETLVHEA-PRVB_CYPCA LQNFKADARALTDGETKTFLKAGDSDGDGKIGVDEFTALVKA--PRVB_BOACO LQNFDGKARDLTDKETAEFLKEGDTDGDGKIGVEEFVVLVTKG-PRV1_SALSA LQNFCPKARELTDAETKAFLKAGDADGDGMIGIDEFAVLVKQ--PRVB_LATCH LQNFSAGARTLTKTETETFLKAGDSDGDGKIGVDEFQKLVKA--PRVB_RANES LQNFRASARVLSDAETSAFLKAGDSDGDGKIGVEEFQALVKA--TPCS_RABIT FR---ASGEHVTDEEIESLMKDGDKNNDGRIDFDEFLKMMEGVQTPCS_PIG FR---ASGEHVTDEEIESIMKDGDKNNDGRIDFDEFLKMMEGVQTPCC_MOUSE LQ---ATGETITEDDIEELMKDGDKNNDGRIDYDEFLEFMKGVE

:: .. :: : :: .* :.** *. :** ::


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Going further…

PRVA_MACFU VGAFSAIDS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGFIPRVB_BOACO LQSCQAADS--FSCKTFFAKSG------LHSKSKDQLTKVFGVIDRDKSGYIEEDELKKFPRV1_SALSA LEACKAADT--FSFKTFFHTIG------FASKSADDVKKAFKVIDQDASGFIEVEELKLFTPCS_RABIT IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNADGYIDAEELAEITPCS_PIG IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNMDGYIDAEELAEITPCC_MOUSE IDEVDEDGSGTVDFDEFLVMMVRCMKDDSKGKSEEELSDLFRMFDKNADGYIDLDELKMMTPC_PATYE SDEMDEEATGRLNCDAWIQLFER---KLKEDLDERELKEAFRVLDKEKKGVIKVDVLRWI

. : .. . :: . : * :* : .* *. : * .

PRVA_MACFU LKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAES--PRVB_BOACO LQNFDGKARDLTDKETAEFLKEGDTDGDGKIGVEEFVVLVTKG--PRV1_SALSA LQNFCPKARELTDAETKAFLKAGDADGDGMIGIDEFAVLVKQ---TPCS_RABIT FR---ASGEHVTDEEIESLMKDGDKNNDGRIDFDEFLKMMEGVQ-TPCS_PIG FR---ASGEHVTDEEIESIMKDGDKNNDGRIDFDEFLKMMEGVQ-TPCC_MOUSE LQ---ATGETITEDDIEELMKDGDKNNDGRIDYDEFLEFMKGVE-TPC_PATYE LS---SLGDELTEEEIENMIAETDTDGSGTVDYEEFKCLMMSSDA

: . :: : :: * :..* :. :** ::


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What makes a good alignment…

The more divergent the sequences, the betterThe fewer indels, the betterNice ungapped blocks separated with indelsDifferent classes of residues within a block:

Completely conserved (*)Size and hydropathy conserved (:)Size or hydropathy conserved (.)

The ultimate evaluation is a matter of personal judgment and knowledge


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Avoiding pitfalls


CN+LF-2003.10

Naming your sequences the right way

Never use white spaces in your sequence namesNever use special symbols. Stick to plain letters, numbers and the underscore sign (_) to replace spaces. Avoid ALL other signs, especially the most tempting ones like @, #, |, *, >,


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Beware of RepeatsThere is a problem when two sequences do not contain the same number of repeats

It is then better to manually extarct the repeats and to align them separately. Individual repeats can be recognized using Dotlet or Dotter.


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Keep a biological perspectivechite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKDwheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSEtrybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGPmouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP

***. ::: .: .. . : . . * . *: *


* : .* . :

chite AD--K----PKR-PLYMLWLNS-ARESIKRENPDFK-VT-EVAKKGGELWRGL-wheat -DPNK----PKRAP-FFVFMGE-FREEFKQKNPKNKSVA-AVGKAAGERWKSLStrybr -K--KDSNAPKR-AMT-MFFSSDFR-S-KH-S-DLS-IV-EMSKAAGAAWKELG mouse ----K----PKR-PRYNIYVSESFQEA-K--D-D-S-AQGKL-KLVNEAWKNLS

* *** .:: ::... : * . . . : * . *: *

chite KSEWEAKAATAKQNY-I--RALQE-YERNG-G-wheat KAPYVAKANKLKGEY-N--KAIAA-YNK-GESAtrybr RKVYEEMAEKDKERY----K--RE-M-------mouse KQAYIQLAKDDRIRYDNEMKSWEEQMAE-----

: : * : .* :

DIFFERENTPARAMETERS


CN+LF-2003.10

Do not overtune!!!

DO NOT PLAY WITHPARAMETERS!

IF YOU KNOW THE ALIGNMENT YOU

WANT: MAKE IT YOURSELF!


***. ::: .: .. . : . . * . *: *


* : .* . :

chite ---ADKPKRPL-SAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKDwheat --DPNKPKRAP-SAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSEtrybr KKDSNAPKRAMTSFMFFSSDFRS-----KHSDLS-IVEMSKAAGAAWKELGPmouse -----KPKRPR-SAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP

***. * .: .. . : . . * . *: *


* : .* . :


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BaliBase classification and benchmarkDescriptionPROBLEM

Even Phylogenic Spread.

One Outlayer Sequence

Two Distantly related Groups

Long Internal Indel

Long Terminal Indel


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Choosing the right method

Source: BaliBase

Thompson et al, NAR, 1999

PROBLEM Strategy Strategy

ClustalW, T-coffee,MSA, DCA

PrrP,T-Coffee

Dialign II

T-Coffee

T-Coffee

Dialign II

T-Coffee


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Some interesting links


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Conclusion

The best alignment method:Your brainThe right data

The best evaluation method:Your eyesExperimental information (SwissProt)

Choosing the sequences well is importantBeware of repeated elements

What can I conclude?Homology -> information extrapolation

How can I go further?PatternsProfilesHMMs…

an introduction to multiple alignments · institut suisse de bioinformatique cn+lf-2003.10 what do...

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