decay index (kõduindeks) - kui monofüleetiline klaad esinebkõigis puudes, mis on 5 sammu pikemad kui MP puu,aga mitte kõigis, mis on 6 sammu pikemad, siis selleklaadi kõduindeks on 6

1 ACACACACACACACT2 CACACACACACACAT3 CACACACACACACAC4 TACACACACACACGC

ainus informatiivne positsioon

1

2

3

4

MP puu

2. 143. 15 14. 15 3 2

2 3 4 1

1 ACACACACACACAC-T2 -CACACACACACACAT3 -CACACACACACACAC4 -TACACACACACACGC

viga joondamises või järjestuse lugemises

puude juurimine

puude juurimine

MRCA

puude juurimine

puude juurimine

juure leidmine kaasaegsele inimesele

NJ

MP

networks

consensus trees

network as consenus

võrk väljendab lahendamatust (ambiguity)

kaks andmete poolt võrdselt toetatud puud

network as consenus

66

5570 100

66

66

5570 100

66

66

5570 100

66

33

45

networks

0<s<2n-1

splits

H, C, G, O, B

10 taksoni puhul < 512 juurimata puid >2 miljoni juuritud puid >34 miljoni

networks

H CG

O B

28 posO BG

HC

13 posO BH

GC

12 pos

spectral analysis

spectral analysis

puu:Hadamardtransformation

(Hendy, Penny 1993)

expectedspectrum:

reversible

spectral analysis

networks

parallelisms

A

B

C

D

10 6

1

7

3 9

TL=1+10+6+7+3+9=36

dBC=11 17A

B

C

D

11 4

3

7

16

TL=11+3+4+7+16=41

ghost link

networks

Excoffier, Smouse 1994: minimum spanning trees, networks (MSN)

networks

TC TT

CC CT

TC TT

CC CT

TC TT

CC CT

TC TT

CC CT

TC TT

CC CT

networks

TCC TTC

CCC CTC

TTT

CTT

15 trees

networks

4 x 4 x 4 = 64 trees

networks

Nuu-Chah-Nulth(Ward et al. 1991)

896 MP trees(Bandelt et al. 1995)

Networks and tie trees

A C

B D

F

E

A C

B D

F

E

root

E FDB A CE FDB A C

16

9

10

207

5

73

11

3

2

1

22

2 1

1

1

1

1

4

1

2

1

Estonians, n=53

Russians, n=14

Finns, n=11 (Zerjal et al. 1997)

Yakuts, n=18 (Zerjal et. al 1997)

3

11

DYS 391"283"

DYS 391"291"

DYS 19"202"

DYS 19"186"

DYS 390"219"

DYS 390"207"

Buryats, n=22 (Zerjal et. al 1997)

1

1

Armenians, n=9

1

1

1

1

1

1

2

1

Slovaks, n=2

Turks, n=1

variation in Y-chromosome haplogroup 16 (Tat C): 3 STR loci

networks

median networks

1 21

1

2

3

1

3

2

4

median networks (MN)

1

3

2

4

1

3

2

4data

n dimensionalhypercube

median network mapping all the actual data withconsensus (median) vectors

median networks (MN)

a) 000b) 011c) 101

a

b c

100010

111

a

b c

001

MN includesconsensusvector ofthe triplet‘median vector’

‘inetermediate vector’

median networks (MN)

10000100 0010

0001

101

011

000

110

networks

median vectors

binary (0,1) data quaternary (A,C,G,T) data

AC, GGCG, AA

CC, GA

AC

T

RM networks

split decomposition

expansion

networks

networks

Reduced Median (RM) networks

pre-processing: w (weight)

RM networks

Bandelt et al. 2000

RM networks: reduction

Bandelt et al. 2000 ”Speedy constructions, greedy reductions”

Network20D http://www.fluxus-engineering.com/

RM networks: reduction

Bandelt et al. 2000 ”Speedy constructions, greedy reductions”

RM networks: reduction

Bandelt et al. 2000 ”Speedy constructions, greedy reductions”