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Association mapping with high density marker panels
Jeffrey Barrett
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Outline
Linkage disequilibrium and recombination
HapMap
‘Tag’ SNPs
Basic association
Practical
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Linkage disequilibrium
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Linkage disequilibrium
time
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Indirect association
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Measuring LD
locus 1
locu
s 2
D = 11 - pq
r2 = D2/p(1-p)q(1-q)
D´ = D/DMAX
p 1-p
q pq (1-p)q
1-q p(1-q) (1-p)(1-q)
p 1-p
q 11 12
1-q 21 22
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Theoretical and empirical LD
Reich et al. Nature (2001)
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LD analysis with Haploview
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Genotypes vs haplotypes
Genotypes: AA CT CC GA
Haplotypes: ACCG / ATCA
ACCA / ATCG
ATCG / ACCA
ATCA / ACCG
2n possible reconstructions n = number of heterozygous sites
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Limited haplotype diversity
Daly et al, Nat Genet (2001)
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Visualizing empirical LD
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Haplotype blocks
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Haplotype blocks
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Haplotype blocks
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Haplotype blocks
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D´ and r2
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D´ in 100kb
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D´ in common SNPs, 100kb
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r2 in 100kb
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HapMap
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HapMap samples
90 Yoruba individuals (30 parent-parent-offspring trios) from Ibadan, Nigeria (YRI)
90 individuals (30 trios) of European descent from Utah (CEU)
45 Han Chinese individuals from Beijing (CHB)
45 Japanese individuals from Tokyo (JPT)
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Why multiple populations?
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HapMap SNPs
PHASE I: 1,000,000 successful SNPs across the genome
PHASE II: 5,000,000 additional SNPs attempted
~4,000,000 total polymorphic SNPs genomewide
Panel %r2 > 0.8 max r2
YRI 81 0.90CEU 94 0.97CHB+JPT 94 0.97
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Enabling association studies:dbSNP
International HapMap Project. Nature (2005).
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Tagging
Reference panel: HapMap data
Tags: SNPs chosen for genotyping with the aim of capturing as much information as possible
Tests: statistical tests for association to disease
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Pairwise tagging
Tags:
SNP 1SNP 3SNP 6
3 in total
Test for association:
SNP 1SNP 3SNP 6
A/T1
G/A2
G/C3
T/C4
G/C5
A/C6
high r2 high r2 high r2
AATT
GC
CG
GC
CG
TCCC
ACCC
GC
CG
TCCC
GGAA
GGAA
Carlson et al. (2004) AJHG 74:106
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Testing tags for association
Genotype tags in cases and controls
Each tag is tested for association
How can we better use this information?
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Tags:
SNP 1SNP 3SNP 6
3 in total
Test for association:
SNP 1SNP 3SNP 6
Use of haplotypes can improve genotyping efficiency
Tags:
SNP 1SNP 3
2 in total
Test for association:
SNP 1 captures 1+2SNP 3 captures 3+5
“AG” haplotype captures SNP 4+6
AATT
GC
CG
GC
CG
TCCC
ACCC
GC
CG
TCCC
GGAA
GGAA
ACCC
A/T1
G/A2
G/C3
T/C4
G/C5
A/C6
de Bakker et al. (2005) Nat Genet 37:1217
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Efficiency
de Bakker et al. (2005) Nat Genet 37:1217
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Transferability among populations
CEUCEU
Whites fromLos Angeles, CA
Whites fromLos Angeles, CA Botnia, FinlandBotnia, Finland
CEUCEUCEUCEU
Utah residents with European ancestry
(CEPH)
Utah residents with European ancestry
(CEPH)
PIW de Bakker et al.
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Genome-wide tagging coverage
Barrett and Cardon, Nat Genet (2006).
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Population structure
Marchini, Nat Genet (2004)
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Population structure -
BD 1.15
CAD 1.08
HT 1.09
CD 1.26
RA 1.06
T1D 1.07
T2D 1.10
Genomic control - genome-wide inflation of median test statistic
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Crohn’s collection center
Center 3: = 1.77
All others: = 1.09
Center
1
No. of samples
524
2 271
3 439
4 465
5 301
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IBS clustering
Compute IBS between all pairs of individuals, as well as 270 HapMap samples
Create a distance matrix of (1-IBS)
Classical multidimensional scaling generates principal components which capture largest fraction of variation
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Crohn’s PCA
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Genotype calling
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Calling wrinkles: > 3 clusters
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Plate effects
Transition to SSF site
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Association: allelic 2
Case Control
A 70 90
T 30 10Assumes:
multiplicative
HW equilibrium
2 (O E)2
E
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Haploview practical
www.hapmap.org
1. Find bounding hotspots for CARD15 (>10 cM/Mb)
2. Download file for this window
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Haploview practical
1. What fraction of the dataset can be captured with 8 pairwise tags?
2. How much more information can be gained by using multimarker tagging?
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Haploview practical
Data in F:\barrett
Is our result experiment-wide significant?