haplotype trees using the evolutionary history of small dna regions to investigate common diseases
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Haplotype Trees
Using The Evolutionary History of Small DNA Regions To
Investigate Common Diseases
Replication
Coalesence
Unrooted Haplotype Tree
Intra-Allelic Sequence Variation (ApoE)
Chimp CCACATGGGCGGTTCCCCCA? GT
10 . . . . . . . . . . . . . . . . T . T . T. 1 0 1 2 416 . . . . T. . . . . . . . . . . T . T . T. 1 0 0 1 2ε2 22 . . . . TC. . . T . . . . . . T . T . T . 0 0 0 1 19 . . . . . C. . . . . . . . . . T . T . T . 0 0 1 4 524 . . . . . C. . . . . . . . . . T . T T T . 0 0 0 1 1
26 . . . . TCTC. . . . . . . . T . . . . . 0 0 0 1 121 . . . . . CTC. T . . . . . . T . . . . . 0 0 0 1 14 . . . . T . TC. . . . . . . . T . . . . . 1 5 2 8 1629 . . . . . . TC. . . . . . . GT . . . . . 0 1 0 0 11 . . . . . . TC. . . . . . . . T . . . . . 8 19 11 7 4530 . . . . . . TC. . . . G. . . T . . . . . 0 0 1 0 114 . . . . . . TCA. . . . . . . T . . . . C 0 0 2 0 219 . . . . . . . C. . . . . . . . T . . . . . 1 0 0 0 1
ε3 6 . . . . . . . . . . . . . . . . T . . . . . 3 5 0 0 827 . T . . T . . . . . . . . . G. T . . . . . 1 0 0 0 18 . . . . T . . . . . . . . . . . T . . . . . 2 3 0 0 53 . . . . T . . . . . . A. . . . T . . . . . 8 3 3 1 1511 . . . . . C. . . . . A. . . . T . . . . . 0 0 0 2 22 . . . . . . . . . . . A. . . . T . . . . . 15 6 11 11 4328 . . . T . . . . . . . A. . . . T . . . . . 1 0 0 0 17 . . . . . . . . . . . A. . . . T . . . . C 1 1 4 2 825 . . . . . . . . . . AA. . . . T . . . . C 0 0 1 0 1
17 T . . . . . . . . . . . . . . . . T . . . . 2 0 0 0 212 . . . . . . . . . . . . . . . . . . . . . . 1 0 0 1 213 . . . . T . . . . . . . . . . . . . . C . . 0 0 1 1 220 . . G. T . T . . . . . . . . . . . . . . . 1 0 0 0 1ε423 . . G. . . T . . . . . . . . . . . . . . . 1 0 0 0 115 . . . . . CT . . . A. . . . . . . . . . . 0 0 0 2 218 . . . . . . T . . . A. . . . . . . . C . C 0 0 1 0 15 . . . . . . T . . . A. . . . . . . . . . . 0 5 9 1 15
J C N R T
13 (6.8%)
152 (79.2%)
27 (14%)
31 . . . . . . T . . . A. . C. . . . . . . . 0 0 0 1 1
21
Statistical Vs. Maximum Parsimony
A = AGCTB = TGCTC = TACTD = AAGG
A B
CD
MaximumParsimony
1A↔1T
1A↔1T
2G
2A
2G
2A
3G↔3C 4G↔4T
A B
CD
1A↔1T
1A↔1T
2G
2A
2G
2A
3G↔3C 4G↔4T
StatisticalParsimony
The Apo-protein E Haplotype
Tree
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
ε3
ε2
ε4
What Use Are Haplotype Trees?
• Provides an Interpretive Framework When Integrated With Other Analyses
• Evolutionary History Generates Hypotheses About Current Significance
• Provides a Powerful Tool For Detecting Current Genotype-Phenotype Associations
A Haplotype Tree Can Provide an Interpretive Framework When Integrated With Other Analyses
0.0
2.0
4.0
6.0
g056
0 g0
624
g393
7 g4
951
g244
0 g5
361
g244
0 g4
075
g199
8 g3
937
g116
3 g5
361
g083
2 g4
075
g244
0 g4
951
g393
7 g4
075
g199
8 g4
075
g056
0 g3
106
g056
0 g5
361
g116
3 g4
075
g407
5 g5
361
g083
2 g4
951
g116
3 g2
440
g290
7 g3
937
g199
8 g2
907
g244
0 g2
907
g083
2 g3
937
g062
4 g1
163
g062
4 g1
998
g083
2 g5
361
g152
2 g2
440
g062
4 g3
937
g083
2 g2
907
g062
4 g0
832
g116
3 g1
998
g116
3 g3
937
g056
0 g4
075
g083
2 g1
522
g083
2 g3
106
g116
3 g1
522
g062
4 g4
075
g244
0 g3
106
g310
6 g5
361
g116
3 g3
106
g199
8 g4
951
g083
2 g1
998
g056
0 g1
998
g199
8 g2
440
g083
2 g2
440
g393
7 g5
361
g199
8 g5
361
g116
3 g4
951
g244
0 g3
937
g056
0 g3
937
g062
4 g5
361
g062
4 g2
440
g083
2 g1
163
g056
0 g2
440
g056
0 g0
832
g056
0 g1
163
560- 1163**
560-832**
560-2440**
832-1163**
3937-4075
8.0
Hamon and Sing estimated interactions for all 53 pairs of ApoE sites for lnApoE variability
in North Karelia, Females
R2
X 1
00
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
Sites IdentifiedBy Hamon and
Sing That“Interact”
With Site 560
ParallelMutations
At Site560
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
EvolutionaryHypothesis:
Two FunctionalMutations (Occurring
On A SpecificHaplotype
Background)Have Created
Three Allelic CladesFor the PhenotypeOf ln(ApoE); the
Red, Blue and BlackClades
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
The Red Clade IsUniquely Defined
By These Two Sites
The Blue Clade Is Uniquely Defined By
These Two Sites
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
The Red Clade IsNot Uniquely DefinedBy These Two SitesDue to Homoplasy
The Apo-protein E Haplotype
Tree
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
Sites 560 and 624Fall into an Alu Repeat
Single SNP Analysis of lnApoE in North Karelia, females
**
73 308
471545560624832
1163
15221575
1998
2440
2907
3106
3673
393740364075
4951
5229a5229b5361
Exon 1 Exon 2 Exon 3 Exon 41 Kb
Indicates a significant single site effect*
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
The Single SNPAnalysis Identifies
Sites With A WeakerPhenotypic
Association BecauseIt Cannot Deal WithHomoplasy At Site
560
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
The Single SNPAnalysis Identifies
Sites With A WeakerPhenotypic
Association BecauseIt Cannot Deal WithHomoplasy At Site
560
There is a deliberate attemptTo find SNPs that are
Polymorphic in most or allPopulations and that have
High heterozygosities; that is,SNPs just like the one at
Site 560.
Linkage Disequilibrium Is Frequently Used in Association Studies, But Also Is Frequently
Misinterpreted.Haplotype Trees Can Aid In Understanding The Proper Biological Interpretation
ApoE Gene
Stengård et al. (1996) showed the amino acid replacement alleles at ApoE have a major impact on mortality due to CAD in a longitudinal study.
0
1
2
3
4
5
6
7
CAD MortalityRelative to
CAD Mortalityof 3/3
3/33/42/4 & 4/4
Apoprotein E Gene Region
0. 0.5 1. 1.5 2. 2.5 3. 3.5 4. 4.5 5. 5.5
Exon
1
Exon
2
Exon
3
Exon
4
73 308
471
545
560
624
832
1163
1522
1575
1998
2440
2907
3106
3673
3937
4036
4075
4951
5229
A52
29B
5361
3701*
Apoprotein E Gene Region
0. 0.5 1. 1.5 2. 2.5 3. 3.5 4. 4.5 5. 5.5
Exon
1
Exon
2
Exon
3
Exon
4
73 308
471
545
560
624
832
1163
1522
1575
1998
2440
2907
3106
3673
3937
4036
4075
4951
5229
A52
29B
5361
3701*
These Two Sites Are in Disequilibrium
The Apo-protein E Haplotype
Tree
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
The Apo-protein E Haplotype
Tree
560
560
560
560560
560
1575
624
624624
624
1522
5361
5361
5361
4951
4951
4951
832
83224401998 1998
3937
5229B
4075
1163 4036
73
471
14
1119
17 20 18
23
1512
25
13
10 16
24
2
22
67 5
1
1575
560
624
624
21
26
4
3
31
3106
28545
27 3673
308
29 3701
8
30
2907
9
These haplotypes Are T at Site 832 &
C At Site 3937
These haplotypes Are G at Site 832 & T At Site 3937
Apoprotein E Gene Region
0. 0.5 1. 1.5 2. 2.5 3. 3.5 4. 4.5 5. 5.5
Exon
1
Exon
2
Exon
3
Exon
4
73 308
471
545
560
624
832
1163
1522
1575
1998
2440
2907
3106
3673
3937
4036
4075
4951
5229
A52
29B
5361
3701*
Site 3937 Is An Amino Acid Polymorphism That Affects ApoE
Function and CAD
Apoprotein E Gene Region
0. 0.5 1. 1.5 2. 2.5 3. 3.5 4. 4.5 5. 5.5
Exon
1
Exon
2
Exon
3
Exon
4
73 308
471
545
560
624
832
1163
1522
1575
1998
2440
2907
3106
3673
3937
4036
4075
4951
5229
A52
29B
5361
3701*
Site 3937 Is An Amino Acid Polymorphism That Affects ApoE
Function and CAD
Suppose Only This Portion Was Sequenced
Apoprotein E Gene Region
0. 0.5 1. 1.5 2. 2.5 3. 3.5 4. 4.5 5. 5.5
Exon
1
Exon
2
Exon
3
Exon
4
73 308
471
545
560
624
832
1163
1522
1575
1998
2440
2907
3106
3673
3937
4036
4075
4951
5229
A52
29B
5361
3701*
Site 3937 Is An Amino Acid Polymorphism That Affects ApoE
Function and CAD
Suppose Only This Portion Was Sequenced
Site 832 Would Appear to Have TheStrongest Association with ApoE
Function and CAD
Apoprotein E Gene Region
0. 0.5 1. 1.5 2. 2.5 3. 3.5 4. 4.5 5. 5.5
Exon
1
Exon
2
Exon
3
Exon
4
73 308
471
545
560
624
832
1163
1522
1575
1998
2440
2907
3106
3673
3937
4036
4075
4951
5229
A52
29B
5361
3701*
Suppose Only This Portion Was Sequenced
Site 832 Would Have TheStrongest Association with ApoE
Function and CAD
Apoprotein E Gene Region
0. 0.5 1. 1.5 2. 2.5 3. 3.5 4. 4.5 5. 5.5
Exon
1
Exon
2
Exon
3
Exon
4
73 308
471
545
560
624
832
1163
1522
1575
1998
2440
2907
3106
3673
3937
4036
4075
4951
5229
A52
29B
5361
3701*
Suppose Only This Portion Was Sequenced
Site 832 Would Have TheStrongest Association with ApoE
Function and CAD
Would you infer
From this Association
That the Marker Closest
to the Functional Site
WasHere?
Haplotype Trees Estimate an Evolutionary History That Can
Generate Hypotheses About The Current Significance of Genetic
Variation
73R
55N
52N
1JNR 2JNR
56N
61N
9N
53N
60N
4JN
79R
64J
70R
43J
27J
11J
28J
59N
23J
31J 19J
16J
10J
30J
74R 83R
5NR3JNR 7NR
85R54N41N
42N
57J22J35J
8J
14J
40J
37J
44N
76R
56 59 45
29
637
8
13
317 38
7
8
13
63
38
20
27
26
51N29335663
31
5920
44 19
305033
31
38
54
30
50
3050
60616566
64
2642
26
4256
29 31 33 5659
53 13
65
46
29
7 8
26
53
2565 19 61
58
6566
8
29
8
8 25
6340
5367
24J34J26
4
63
5
1666
41
29 36 69
17J
9
10
19
2 17
14
T-1
36J
5
12
16
31
35
38
39
41
43
44
46
47
60
57
64
T-4
6
15J 33J15
186365
3469
63N
71R 47N
66N
4
45J
19
20
26
27
5359
78
13
6869
62
9
10
11
16
17
214
23
53
69
13J 72R15233469
5958N 75R
53
19 2935365557586138J
5155
T-3
T-240
454968
32374852
29J
19
44
5
9
10
2
16
17222428354155
6
18
558
44
16
19
8 12J80R18J 25J30 35 36 46 58
33
330
55
4981R
39J
77R
67N
48N44
2642
40
53
2741
49N
62N65N
69R
84R
50N
21J
78R46N
20262729
3050
78132933
86R62
35
41323
44
53
4453
30 50
172642
6NR68R
88R
9
10111721232915
4
2627
5
26J
14
15
6
614
6
2832J
1940293536
41
58
67
3
18
25
30
4920J 5 16 19 31 56
a
b
cd
e
f
g
255387R82R
29 4511172123 3159h ij
k
l
m
n
p
q
r
s
t
u
v
w
x
LPL Tree
5NR
2JNR 79R70R
7
8
13
20
29 31 33 56 53
5
65
25
7 813
16
11J
611931J
66 29 36 69
5
16
12
36J
Branch "A"
{
Detecting Recombinantion Events in LPL
=3, =5, =3, p =0.0179, crossover between sites 13 and 29.1 10 20 30 40 50 60 69
2JNR CAGTTTCCCT CAGCACGATC GCAATTGCAC CTCAATGTAT AGTTGTAACC GAGTCCGCAT AACTATAGG5NR CAGTTTATCT CACCACGATA GCAATTGCAC CTCAATGTAT AGTTGTAACC GAGTCCGCAT AACTATAGGNode a CAGTTTATCT CACCACGATC GCAATTGCTC TTTAATGTAT AGTTGTAACC GAATCAGCAT AACTATAGG
=2, =7, =2, p =0.0278, crossover between sites 16 and 19.
Node d CAGTTTATCT CACCACGATC GCAACTGCTC TTTAATGTAT AGTTGTAACC GAATCAGCAT AACTATAGG11J CAGTATATCT CACCATGATC GCAACTGCTC TTTAATGTAT AGTTGTAACC GAATCAGCAT AACTATAGGNode e CAGTATATCT CACCATGAGC GCAATTGCAC TTTAA?GTAT AGTTGTAACC GAATCAGCAT CACTGGAGA
11J CAGTATATCT CACCATGATC GCAACTGCTC TTTAATGTAT AGTTGTAACC GAATCAGCAT AACTATAGGNode e CAGTATATCT CACCATGAGC GCAATTGCAC TTTAA?GTAT AGTTGTAACC GAATCAGCAT CACTGGAGAT-1 CAGTTTATCT CACCACGAGC GCAATTGCAC TTTAA?GTAT AGTTGTAACC GAATCAGCAT CACTGGAGA
Linkage Disequilibrium & TheRecombinational Hotspot in LPL
Haplotype Network in 5’ Region of LPL
5'-1 5'-2 5'-823J
8J14J44N
3
17
13 7 84
5 16 9 10 2
14
36J12
6
15
188
49N
84R
175'-3
5'-4
17
5'-5
5'-6
5'-7
16
4
4
6
32J
9 10
Haplotype Network in 3’ Region of LPL
3'-9
56N
53N
3'-4
64J 43J
59N
3'-12 19J
16J
30J
54N
41N 42N
40J
37J
59 44
50 38 54
50
64
42
65
4661
58
6566
6340
53 6724J34J
4136 69
T-136J
38 39 41 43 44 46 47 60 5764T-4
69
3'-10
3'-11
45J
53
59
75R
53
36
55
58
61
38J
51
55
40
45
3756
3'-8
8J 14J
T-3
48
52
29J44
55
35J
41
T-2
49
68
12J
3'-636
46
58 55
49
81R
39J
49N
50N
78R
46N
503'7
62
4450
26J
61
32J40
36
41 58 67
49 20J
77R
67N 48N
42
41
62
59
3'-161N
60N
56
59 45 63 3'-2
9N44N
38 3863
56 56
3'-351N 63
63 3'-5
53 53
28J
4259 45
5544
40 53
42
53
42
Neutral Genetic Drift, Stable
Population Size
Neutral Genetic Drift, Expanding Population Size
Negative Selection
Positive (Directional) Selection or Bottleneck
Positive (Diversifying) Selection or Subdivision
Peeled Haplotype Network in of LPL
52N
1JNR 2JNR
56N
61N
9N
53N
60N
4JN
79R
64J
70R
43J
27J
11J
28J
59N
23J
31J 19J
16J
10J
30J
40J
37J
56 59 45
29
63
38
30
50
3050
64
2642
26
4256
29 31 33 5659
53 13
65
46
29
7 8
26
53
2565 19 61
58
6566
8
29
8
8 25
6340
5367
34J26
4
63
5
1666
41
29 36 69
17J
9
10
19
2 17
T-1
36J
5
12
16
31
35
38
39
41
43
44
46
47
60
57
64
T-4
5155
T-3
T-240
454968
32374852
29J
19
44
Evolutionary Inferences On LPL
• 5’ End Subject to Directional Selection, With A Selective Sweep Enhanced By Recombination
• 3’ End Subject to Diversifying Selection
• Implies That Most Current Polymorphisms With Functional Significance Are In 3’ End
Haplotype Trees Provide a Powerful Tool For Detecting Current Genotype-Phenotype
Associations
• Nested Clade Analysis
• Tree Scanning
Nested Clade Analysis
• In 1987 Published The Nested Clade Method For Using A Haplotype Tree As A Tool For Discovering Gene/Phenotype Associations
• Nests The Haplotypes in Tree Into Evolutionary Clades (Branches)
• The Resulting Nested Design Provides Asymptotic Independence And A Priori Contrasts For Detecting Phenotypic Associations.
The Drosophila Adh Haplotype Tree
The Drosophila Adh Haplotype Tree
1-11-2
1-3
1-4
1-5
1-6
1-7
1-8
1-9
1-10
1-11
The Drosophila Adh Haplotype Tree
2-1
2-2
2-3
2-4
2-5
The Drosophila Adh Haplotype Tree
3-1
3-2
Results of Nested Analysis of Variance of Adh Activity Using The Adh Haplotype Tree
***
**
**
**
** Significant at 1% Level*** Significant 0.1% Level
Functional Allelic Categories from the Nested Analysis of Variance of Adh Activity
***
**
**
**
Phenotypic Distributions Identified Though Nested Clade Analysis
0
1
2
3
4
5
6
7
8
9
2.14 2.64 3.14 3.64 4.14 4.64 5.14 5.64 6.14 6.64 7.14 7.64 8.14 8.64 9.14 9.64 10.1
Adh Activity
Number of Lines
Clade 1-4 Remainder 3-1
0
1
2
3
4
5
6
7
8
9
2.14 2.64 3.14 3.64 4.14 4.64 5.14 5.64 6.14 6.64 7.14 7.64 8.14 8.64 9.14 9.64 10.1
Adh Activity
Number of Lines
Clade 3-1 Clade 3-2
0
1
2
3
4
2.14 2.64 3.14 3.64 4.14 4.64 5.14 5.64 6.14 6.64 7.14 7.64 8.14 8.64 9.14 9.64 10.1
Adh Activity
Number of Lines
Haplotype 19 Haplotype 23 Remainder 3-2
Nested Clade Analyses
• Greater Statistical Power By Focusing On Fewer Comparisons
• Greater Biological Power In Detecting Mutations With Phenotypic Effects
• Deals With High Levels of Genetic Variation Through Pooling Into Clades
• Deals With Linkage Disequilibrium Through Haplotypes And Tree Branches
• Useful In Ultimately Identifying Causative Mutations
Nested Clade Analyses
• Although Nesting Is Common In Statistics and Evolutionary Biology, It Is Unfamiliar and Daunting To Others
• The Analysis Finds Phenotypic Associations With Haplotypes or Groups of Haplotypes: Does Not Deal Directly With Dominance Effects Or Genotypes.
• Is Inherently A Single Locus (Or Smaller) Analysis: Does Not Deal Directly With Epistasis
Tree Scanning
A New Method for Using Haplotype Trees At Candidate Loci To Investigate Genotype-
Phenotype Associations.
E.g., A Genome Scan for Lupus (Gray-McGuire et al. 2000)
Tree Scanning
• Make All Possible Bi-Allelic Partitions of the Haplotype Tree.
• Test For Phenotypic Heterogeneity Among the Resulting Genotypes Using Standard Statistics (ANOVA, t-Tests, Etc.)
• Because Tests Are Not Independent Across The Bi-Allelic Partitions, Randomly Permute Phenotypes Across Genotypes 10,000 Times To Determine the Treewise Type I Error Rate
Scanning The Drosophila Adh Haplotype Tree
Scanning The Drosophila Adh Haplotype Tree
Scanning The Drosophila Adh Haplotype Tree
Significant Results of Adh Tree Scan(Proportion of Phenotypic Variance Explained)
Sequential Adh Tree Scan(Fix Two or More Alleles From First Scan Defined By Distinct Peaks,
Then Examine All Possible Partitions Into Three Alleles)
Sequential Adh Tree Scan(Fix Two or More Alleles From First Scan Defined By Distinct Peaks,
Then Examine All Possible Partitions Into Three Alleles)
Sequential Adh Tree Scan(Fix Two or More Alleles From First Scan Defined By Distinct Peaks,
Then Examine All Possible Partitions Into Three Alleles)
Sequential Adh Tree Scan(Fix Two or More Alleles From First Scan Defined By Distinct Peaks,
Then Examine All Possible Partitions Into Three Alleles)
Significant Peaks In Second Round of the Sequential Adh Tree Scan (Color Changes)
vs. The Nested Clade Analysis (*)
*
*
*
*
Tree Scanning• Is Less Powerful Statistically Than A Nested Clade
Analysis, But Tends To Identify The Same Functional Allelic Categories
• Is Easier To Implement and Automate Than A Nested Clade Analysis
• Detects Phenotypic Heterogeneity Among Genotypes And Therefore Can Detect Dominance Effects, Etc.
• Is Superior To Single SNP Association Tests• It Is Computationally Feasible To Exhaustively Examine
All Combinations of Bi-Allelic Partitions At Two Separate Genes And Therefore Detect Epistasis
Haplotype Trees
Provide a valuable tool in the investigation of common diseases
whose potential has not yet been fully explored or developed.
Genomic Approaches to Common Chronic Disease
A Research Project Supported by: National Institute of General Medical Sciences (NIGMS), P50-GM65509
U. of MichiganAnn Arbor, MI
Charles F. Sing (PI, Component 4)Sharon L. Kardia
Kathy L. Klos Northwestern U. U. of Alabama
Kiang Liu Heather McCreath O. Dale Williams
Cornell, U.Ithaca, NY
Andrew G. Clark (Component 3)S. Malia Fullerton
U. of Texas Houston, TX
James E. Hixson (Component 1)
U. of Texas Houston, TX
Eric Boerwinkle (Component 2)Myriam Fornage
Craig Hanis
Andrei Rodin
Washington U. St. Louis, MO
Alan R. Templeton (Project Consultant)
Support From MDECODE andA Burroughs-Wellcome Fund
Innovation Award In Functional Genomics Are Gratefully
Acknowledged