SNP Discovery and Analysis: Application to Association Studies Mark J. Rieder, PhD Dana Crawford, PhD Deborah Nickerson, PhD SeattleSNPs PGA July 19-20,

SNP Discovery and Analysis: Application to Association Studies

Mark J. Rieder, PhDMark J. Rieder, PhDDana Crawford, PhDDana Crawford, PhD

Deborah Nickerson, PhDDeborah Nickerson, PhD

SeattleSNPs PGASeattleSNPs PGAJuly 19-20, 2005July 19-20, 2005

Practical Aspects of SNP Association Studies

1. SNP Discovery: Where do I find SNPs to use in my association studies? (e.g. databases, direct resequencing)

2. SNP Selection:How do I choose SNPs that are informative?(i.e. assessing SNP correlation - linkage disequilibrium)

3. SNP Associations:What analyses can I perform after genotyping these SNPs?(e.g. single SNP data, haplotype data)

4. SNP Replication/Function:How is function predicted or assessed. (e.g. nonsynonymous SNPs, conserved non-coding regions (CNS)

transcription factor binding sites, gene expression)

SeattleSNPs Program for Genomic Applications: Overview

Aim 1: To establish a variation discovery resource capable of comprehensive resequencing of candidate genes related to HLBS.

Biological Focus: InflammationBiological Focus: InflammationGenes and Pathways: Coagulation, Complement, CytokinesGenes and Pathways: Coagulation, Complement, Cytokines Interacting PartnersInteracting Partners

SNPs in Candidate Genes

Average Gene Size - 26.5 kb ~ Compare 2 haploid - 1 in 1,200 bp

~130 SNPs (200 bp) - 15,000,000 SNPs

~ 44 SNPs > 0.05 MAF (600 bp) - 6,000,000 SNPs

SeattleSNPs

SeattleSNPs PGA: Candidate Gene SNP Resource

• 4.9 Mb in 47 individuals = 230 Mb total sequence • Define sequence diversity - catalogue all SNPs• Select “optimal” tagSNPs sets • Determine haplotype structure • Provide necessary baseline data for association studies

Warfarin Pharmacogenetics1. Background

• Warfarin characteristics• Pharmacokinetics/Pharmacodynamics• Discovery of VKORC1

2. VKORC1 - SNP Discovery

3. VKORC1 - SNP Selection (tagSNPs)

4. VKORC1 - SNP Testing• SNP/Haplotype Inference• Haplotype Inference, Testing

5. VKORC1 - SNP Replication/Function

Pharmacogenomics as a Model for Association Studies

Reduce variability and identify outliers. Prospective testing

Personalized Medicine

Clear genotype-phenotype link intervention variable responsePharmacokinetics - 5x variation

Quantitative intervention and responsedrug dose, response time, metabolism rate, etc.

Target/metabolism of drug generally knowngene target that can be tested directly with response

Warfarin Background• Commonly prescribed oral anti-coagulant

• In 2003, 21.2 million prescriptions were written for warfarin (Coumadin)

• Prescribed following MI, atrial fibrillation, stroke,venous thrombosis, prosthetic heart valve replacement,and following major surgery

• Difficult to determine effective dosage- Narrow therapeutic range - Monitoring of prothrombin time (INR) - 2.0 - 3.0

- Large inter-individual variation

Add warfarin dose distribution

Patient/Clinical/Environmental Factors

0

10

20

30

40

50

0 2 4 6 8 10 12 14 16

Warfarin Dose (mg/d)

No. of patients

Ave: 5.2 mg/dn = 186European-American30x dose variability

Pharmacokinetic/Pharmacodynamic - Genetic

Vitamin K-dependent clotting factorsVitamin K-dependent clotting factors(FII, FVII, FIX, FX, Protein C/S/Z)(FII, FVII, FIX, FX, Protein C/S/Z)

EpoxideReductase

-Carboxylase(GGCX)

Warfarin inhibits the vitamin K cycle

Warfarin

Inactivation

CYP2C9

Pharmacokinetic

Warfarin Metabolism (Pharmacokinetics)Warfarin Metabolism (Pharmacokinetics)

Major pathway for termination of pharmacologic effect Major pathway for termination of pharmacologic effect is through metabolism of S-warfarin in the liver by CYP2C9is through metabolism of S-warfarin in the liver by CYP2C9

• CYP2C9CYP2C9 SNPs alter warfarin metabolism: SNPs alter warfarin metabolism:

CYP2C9*1 (WT) - normalCYP2C9*1 (WT) - normalCYP2C9*2 (Arg144Cys) - low/intermediateCYP2C9*2 (Arg144Cys) - low/intermediateCYP2C9*3 (Ile359Leu) - low CYP2C9*3 (Ile359Leu) - low

• CYP2C9CYP2C9 alleles occur at a significant minor allele frequency alleles occur at a significant minor allele frequencyEuropean: *2 - 10.7% *3 - 8.5 % European: *2 - 10.7% *3 - 8.5 % Asian: *2 - 0% *3 - 1-2% Asian: *2 - 0% *3 - 1-2% African-American: *2 - 2.9% *3 - 0.8% African-American: *2 - 2.9% *3 - 0.8%

Effect of CYP2C9 Genotype on Anticoagulation-Related Outcomes(Higashi et al., JAMA 2002)

WARFARIN MAINTENANCE DOSE

0

1

2

3

4

5

6

7

8

9

*1/*1 *1/*2 *2/*2 *1/*3 *2/*3 *3/*3

mg Warfarin/day

N 127 28 4 18 3 5

mg

war

fari

n/d

ay

- Variant alleles have significant clinical impact- Variant alleles have significant clinical impact- Still large variability in warfarin dose (15-fold) in *1/*1 “controls”?- Still large variability in warfarin dose (15-fold) in *1/*1 “controls”?

TIME TO STABLE ANTICOAGULATION

CYP2C9-WT ~90 days

*2 or *3 carriers take longer to reach stable anticoagulation

CYP2C9-Variant ~180 days

Analysis of Analysis of IndependentIndependent Predictors of Warfarin Dose Predictors of Warfarin Dose

Variable Change in Warfarin Dose P value

Target INR, per 0.5 increase 21% <0.0005

BMI, per SD 14% <0.0001

Ethnicity (African-American, [Asian]) 13%, [ 10-15%] 0.003

Age, per decade 13% <0.0001Gender, Female 12% <0.0001

Drugs (Amiodarone) 24% 0.007

CYP2C9*2, per allele 19% <0.0001

CYP2C9*3, per allele 30% <0.0001

Adapted from Gage et al., Thromb Haemost, 2004

~ 30% of the variability in warfarin dose is explained by these factors

What other candidate genes are influencing warfarin dosing?What other candidate genes are influencing warfarin dosing?

Vitamin K-dependent clotting factorsVitamin K-dependent clotting factors(FII, FVII, FIX, FX, Protein C/S/Z)(FII, FVII, FIX, FX, Protein C/S/Z)

EpoxideReductase

-Carboxylase(GGCX)

Warfarin acts as a vitamin K antagonist

Warfarin

Inactivation

CYP2C9

Pharmacodynamic

New Target Protein for Warfarin

EpoxideReductase

-Carboxylase(GGCX)

Clotting Factors(FII, FVII, FIX, FX, Protein C/S/Z)

Rost et al. & Li, et al., Nature (2004)

(VKORC1)

5 kb - chr 165 kb - chr 16

Warfarin Resistance VKORC1 Polymorphisms

• Rare non-synonymous mutations in VKORC1 causative for warfarin resistance (15-35 mg/d)• NONO non-synonymous mutations found in ‘control’ chromosomes (n = ~400)

Rost, et. al. Nature (2004)

Warfarin maintenance dose (mg/day)

Inter-Individual Variability in Warfarin Dose: Genetic Liabilities

SENSITIVITYSENSITIVITY

CYP2C9 coding

SNPs - *3/*3

RESISTANCERESISTANCEVKORC1

nonsynonymous coding SNPs

0.5 5 15

Fre

qu

ency

Common Common VKORC1VKORC1

non-coding non-coding SNPs?SNPs?

SNP Discovery: Resequencing SNP Discovery: Resequencing VKORC1VKORC1

• PCR amplicons --> Resequencing of the complete genomic region

• 5 Kb upstream and each of the 3 exons and intronic segments; ~11 Kb

• SeattleSNPs PGA - pga.gs.washington.edu (24 African-Am./23 Europeans)

• Warfarin treated clinical patients (UWMC): 186 European

• Other populations: 96 European, 96 African-Am., 120 Asian

Summary of PGA samples (European, n = 23)Total: 13 SNPs identified 10 common/3 rare (<5% MAF)

Clinical Samples (European patients n = 186)Total: 28 SNPs identified 10 common/18 rare (<5% MAF)

15 - intronic/regulatory7 - promoter SNPs2 - 3’ UTR SNPs3 - synonymous SNPs1 - nonsynonymous

- single heterozygous indiv. - highest warfarin dose = 15.5 mg/d

How does the comprehensive SNP discovery compare to How does the comprehensive SNP discovery compare to what was known for this gene?what was known for this gene?

SNP Discovery: Resequencing Results

dbSNP -NCBI SNP database

SNP Discovery: dbSNP database

SeattleSNPs Resequencing 28 SNPs --> 15 SNPs gene region

10 dbSNPs • 8/10 confirmations

• 3 frequency/genotype data

• 7 new dbSNP entries generated by SeattleSNPs resequencing

• 8 dbSNPs/15 SNPs (~50%)

SNP Discovery: dbSNP database (VKORC1)


Nickerson and Kruglyak, Nature Genetics, 2001

Mar 2005Mar 2005 - 5.0 million (validated - 1/600 bp) - 5.0 million (validated - 1/600 bp)

5.0/10.0 = 50% of all common SNPs (validated)!5.0/10.0 = 50% of all common SNPs (validated)!

SNP discovery is dependent on your sample population sizeSNP discovery is dependent on your sample population size

0.0 0.2 0.3 0.4 0.50.10.0

0.5

1.0

Minor Allele Frequency (MAF)

Fra

ctio

n o

f S

NP

s D

isco

vere

d

2

4824

16

8

96

GTTACGCCAATACAGGTTACGCCAATACAGGGATCCAGGAGATTACCATCCAGGAGATTACCGTTACGCCAATACAGGTTACGCCAATACAGCCATCCAGGAGATTACCATCCAGGAGATTACC{{2 chromosomes2 chromosomes

Rarer and population specific SNPs are found by resequencing


Minor Allele Freq. (MAF)

dbSNP (Perlegen/HapMap) SeattleSNPs

Minor Allele Freq. (MAF)

{ 75%75%50%50%

25%25%

0.00

1.00

2.00

3.00

4.00

5.00

6.00

Jan-03 Mar-03 Jun-03 Aug-03 Oct-03 Jan-04 Mar-04 Jun-04 Sep-04 Jan-05 Mar-05

dbSNP Release

SNPs(millions)

Validated SNPs

SNPs with Genotypes

PerlegenPerlegenDataData

dbSNP: Increasing numbers of SNPs now have genotype datadbSNP: Increasing numbers of SNPs now have genotype data

HapMapHapMapPhase IIPhase IIPerlegenPerlegen

0.00

2.00

4.00

6.00

8.00

10.00

12.00

Jan-03 Mar-03 Jun-03 Aug-03 Oct-03 Jan-04 Mar-04 Jun-04 Sep-04 Jan-05 Mar-05

dbSNP Release

SNPs(millions)

Total Reference SNPsValidated SNPsGenotyped SNPs

Current State of dbSNPCurrent State of dbSNP

Many SNPs left to validate and characterize.Many SNPs left to validate and characterize.

Development of a genome-wide SNP map: How many SNPs?Development of a genome-wide SNP map: How many SNPs?

Nickerson and Kruglyak, Nature Genetics, 2001

~ 10 million common SNPs (>1- 5% MAF) - 1/300 bp~ 10 million common SNPs (>1- 5% MAF) - 1/300 bp

Mar 2005Mar 2005 - 5.0 million (validated - 1/600 bp) - 5.0 million (validated - 1/600 bp)

5.0/10.0 = 50% of all common SNPs validated!5.0/10.0 = 50% of all common SNPs validated!Coming Soon!Coming Soon! 5.0 million validated SNPs with genotypes! 5.0 million validated SNPs with genotypes!

dbSNP Issues:

Not comprehensive catalog (50% of SNPs)

Is the data confirmed? (50% are validated)

Information about allele frequency/population (50%)

No information about SNP correlations (linkage disequilibrium)genotyping efficiency


• Common SNPs• VKORC1 - 28 total - 10 SNPs > 10% MAF

• Evaluate linkage disequilibrium (non-random association ofgenotype data)

Does common variation in VKORC1 have a role in determiningDoes common variation in VKORC1 have a role in determiningwarfarin dose?warfarin dose?

Warfarin Dose (mg/d)

Fre

quen

cy

SNP Selection: Using Linkage Disequilibrium

T G 0.5 X 0.5 = 0.25 0.48 *

C : 50%

T : 50%

A : 50%

G : 50%

Site 1 Site 2

C A 0.5 X 0.5 = 0.25 0.50 * C G 0.5 X 0.5 = 0.25 0.01 T A 0.5 X 0.5 = 0.25 0.01

C

T

A

G

Site 1 Site 2

Maternal

Paternal

* Sites Correlated

Possible2-site comb. Expected Freq. Observed Freq.

SNP Selection: Using Linkage Disequilibrium

SNP Selection: Using Linkage Disequilibrium• SNP discovery data (i.e. population of samples with genotypes)• Find all correlated SNPs to minimize the total number of SNPs• Maintains genetic information (correlations) for that locus

LD_Select - SNP tagging/binning algorithm - based on LD (r2), not haplotypes

Carlson, et al. AJHG (2004)

SNP Selection: VG/LD_Select on the Web

pga.gs.washington.ed/VG2

SNP Selection: tagSNP Data

SNP Selection: VKORC1 tagSNPs

Five Bins to TestFive Bins to Test1.1. 381, 3673, 6484, 6853, 7566381, 3673, 6484, 6853, 75662.2. 2653, 60092653, 60093.3. 8618614.4. 580858085.5. 90419041

Bin 1 - p < 0.001Bin 1 - p < 0.001Bin 2 - p < 0.02 Bin 2 - p < 0.02 Bin 3 - p < 0.01 Bin 3 - p < 0.01 Bin 4 - p < 0.001 Bin 4 - p < 0.001 Bin 5 - p < 0.001Bin 5 - p < 0.001

C/C C/T T/T

e.g. Bin 1 - SNP 381

SNP x SNP interactions - haplotype analysis?SNP x SNP interactions - haplotype analysis?

SNP Testing: VKORC1 tagSNPs

VKORC1 Summary: SNP Discovery/SNP Selection

1. VKORC1 candidate gene for warfarin dose response

2. SNP discovery performed using PCR/resequencing to catalog common SNPs• 28 SNPs found • 10 common SNPs

3. SNP discovery using dbSNP• 8/10 dbSNPs confirmed • 7 new SNPs added

4. SNP Selection using linkage disequilibrium• 10 common SNPs (> 10% MAF)• 5 informative SNPs for genotyping

Haplotypes in Genetic Association Studies

Two main approaches with haplotypes:

Haplotypes Pick tagSNPs Genotype samples

Pick tagSNPs Infer haplotypes Test for association


1. How can you get haplotypes?

2. What information do you get from haplotypes?

3. How do you use haplotypes to find tagSNPs?

4. How do you use haplotypes to test for associations?

Haplotypes – The Definition

“…a unique combination of genetic markers present in a chromosome.” pg 57 in Hartl & Clark, 1997

Constructing Haplotypes

C TA G

T TG G

C CA G

C/T, A/G

C/C, A/GT/T, G/G

C/T, A/AC/C, A/G

Collect pedigrees Somatic cell hybrids

Human Rodent

Hybrid

SNP 1 SNP 2

C/T A/G

Allele-specific PCR

Constructing Haplotypes

Examples of Haplotype Inference Software:

EM AlgorithmHaploview http://www.broad.mit.edu/mpg/haploview/index.php Arlequinhttp://lgb.unige.ch/arlequin/

PHASE v2.1http://www.stat.washington.edu/stephens/software.html

HAPLOTYPERhttp://www.people.fas.harvard.edu/~junliu/Haplo/docMain.htm

http://www.broad.mit.edu/mpg/haploview/index.php

http://lgb.unige.ch/arlequin/

Haplotypes in SeattleSNPs

• >200 genes re-sequenced in inflammation response

• 2 populations: European- and African-Americans

• PHASEv2.0 results posted on website

• Interactive tool (VH1) to visualize and sort haplotypes

http://pga.gs.washington.edu















Pick tagSNPs Infer haplotypes Test for association

RecombinationNatural selectionPopulation historyPopulation demography

Haplotype block definition

Measuring Pair-wise SNP Correlations

• SNP correlation described by linkage disequilibrium (LD)

• Pair-wise measures of LD: D´ and r2

D = pAB - pApB; D´ = D/Dmax Recombination

r2 = D2

f(A1)f(A2)f(B1)f(B2) Power

• r2 is inversely related to power

1/r2

1,000 cases 1,250 cases1,000 controls r2=1.0 1,250 controls r2 = 0.80

• D´ is related to recombination history

D´ = 1 no recombinationD´ < 1 historical recombination

Example: LDSelect

Example: Haplotype “blocks”

Using LD and Haplotypes to Pick tagSNPs

Haplotype “Blocks”

Strong LD Few Haplotypes Represent most chromosomes

Daly et al 2001Daly et al Nat. Genet. (2001)

Block Definitions

Daly et al 2001

D´ [Gabriel et al Science (2002)]

Daly et al Nat. Genet. (2001)

Block Definitions

A B

a bA b

a B

Four-gamete test:

A B

a b

<4 haplotypes, D´=1 block

4 haplotypes, D´<1 boundary

Haplotype Blocks and tagSNPs

Identifying blocks and tagSNPs:

• Manually

• Algorithms– Haploview


IL1B:19 SNPs (MAF >5%)

4 “common” haplotypes

tagSNPs


Identifying blocks and tagSNPs:

• Manually

• Algorithms– HaploView

LD and tagSNPs using Haploview

VKORC1European-Americans

PHASEv2.1 data

Minimal set of tagSNPs based on r2

Where to Find Tagging Software

HaploBlockFinder http://cgi.uc.edu/cgi-bin/kzhang/haploBlockFinder.cgi

LDSelect http://droog.gs.washington.edu/ldSelect.html

SNPtagger http://www.well.ox.ac.uk/~xiayi/haplotype/index.html

TagIT http://popgen.biol.ucl.ac.uk/software.html

tagSNPs http://www-rcf.usc.edu/~stram/tagSNPs.html

Haploview http://www.broad.mit.edu/personal/jcbarret/haplo/

http://cgi.uc.edu/cgi-bin/kzhang/haploBlockFinder.cgi














http://droog.gs.washington.edu/ldSelect.html











http://www.well.ox.ac.uk/~xiayi/haplotype/index.html





http://popgen.biol.ucl.ac.uk/software.html







http://www-rcf.usc.edu/~stram/tagSNPs.html









Haplotypes, TagSNPs, and Caveats

• Haplotypes are inferred

• Block-like structure assumed for some software

• Different block definitions

• Block boundaries sensitive to marker density

• Genotype savings may not be great (recombination)




Pick tagSNPs Infer haplotypes Test for associationGenetic diversity of sampleMulti-SNP analysis

Five tagSNPs (10 total SNPs)Five tagSNPs (10 total SNPs)

186 warfarin patients (European)PHASE v2.1

9 haplotypes/5 common (>5%)

Multi-SNP testing: Haplotypes


Test for association between haplotype and warfarin dose using multiple linear regression

Adjusted for all significant covariates: age, sex, amiodarone, CYP2C9 genotype

CCGATCTCTG-H1 CCGAGCTCTG-H2

TAGGTCCGCA-H8 TACGTTCGCG-H9

(381, 3673, 6484, 6853, 7566) 5808

9041

861

B

A

VKORC1 haplotypes cluster into divergent clades

Patients can be assigned a clade diplotype:e.g. Patient 1 - H1/H2 = A/A

Patient 2 - H1/H7 = A/BPatient 3 - H7/H9 = B/B

Explore the evolutionary relationship across haplotypes

TCGGTCCGCA-H7


VKORC1 clade diplotypes show a strong association with warfarin dose

Low

High

A/AA/BB/B

*

††

**

All patients 2C9 WT patients 2C9 VAR patientsAA AB BBAA AB BB AA AB BB

(n = 181) (n = 124) (n = 57)

Independent of INR levels across all groups

• European - mean ~ 5 mg/d

• African-American - higher ~ 6.0-7.0 mg/d

• Asian - lower ~ 3.0-3.5 mg/d

Hypothesis:Hypothesis: VKORC1VKORC1 haplotypes contribute to racial haplotypes contribute to racial variability in warfarin dosing.variability in warfarin dosing.

• “Control” populations: 120 Europeans 96 African-Americans

120 Asian


Asian (Han) Clade Distribution

Low dose phenotype

A(89%)

B(11%)

African-American Clade Distribution

High dose phenotype

A(14%)

B(47%)

Other(39%)

European (CEPH)Clade Distribution

B(58%)

A(37%)

Clade A = LowClade B = High

Explore the evolutionary relationship across populations


• Small sample size

• Subgroup analysis and multiple testing

• Random error

• Poorly matched control group

• Failure to attempt study replication

• Failure to detect LD with adjacent loci

• Overinterpreting results and positive publication bias

• Unwarranted ‘candidate gene’ declaration after identifying association in arbitrary genetic region

Common Errors in Association StudiesBell and Cardon (2001)

e.g., Second case/control studyGene expression studies

*

††

* *


Univ. of Washingtonn = 185


†

†

*

†

*

21% variance in dose explained

Washington Universityn = 386

Brian GageHoward McCleodCharles Eby

SNP Replication: VKORC1

SNP Function: VKORC1 Expression

mechanism

No nonsynonymous SNPs

Several SNPs are present in evolutionarily conserved non-coding regions

- mRNA expression in human liver cell lines

SNP Function: VKORC1 Expression

Expression in human liver tissue (n = 53) shows a graded change in expression.

VKORC1 SNP alters liver-specific binding siteVKORC1 SNP alters liver-specific binding site

• Databases and resources available for SNP discovery

• Software for tagSNP selection available

• Both single and multi-SNP analysis are useful

• Replication required by several journals

SNP Discovery and Analysis Application to Association Studies

Summary

SeattleSNPs Genotyping Service

• Free genotyping (BeadArray or SNPlex)

• Emphasis on young investigators

• Research related to heart, lung, blood, or sleep disorders

• Moderate to large population samples

• Apply at pga.gs.washington.edu

• Due: October 15th, 2005

SNP Typing Formats

Microtiter Plates - Fluorescence

Size Analysis by Electrophoresis

Arrays - Custom or Universal

eg. Taqman - Good for a few markers - lots of samples - PCR prior to genotyping

eg. SNPlex - Intermediate Multiplexing reduces costs - Genotype directly on

genomic DNA - new paradigm for high throughput

eg. Illumina, ParAllele, Affymetrics - Highly multiplexed- 1,500 SNPs and beyond (500K+)

Low

Medium

High

Scale

Taqman

Genotyping with fluorescence-based homogenous assays (single-tube assay) = 1 SNP/ tube

SNP Typing Formats








Low

Medium

High

Scale

Technological Leap - No advance PCR

Universal PCR after preparing multiple regions for analysis -

Several based on primer specific on genomic DNA followed by PCR of the ligated products - different strategiesand different readouts.

SNPlex, Illumina, Parallele

Also, reduced representation - Affymetrix - cut with restriction enzyme, then ligate linkers and amplify from linkers and follow by chiphybridization to read out.

9. Characterize on Capillary Sequencer

Detection

SNP 1

SNP 2

SNP Typing Formats








Low

Medium

High

Scale

Locus 1 Specific Sequence

cTag1 sequenceTag1 sequence

SubstrateBead or Chip

Tag 1

Tag 2

Tag 3

Tag 4

Chip ArrayBead Array

Multiplexed Genotyping - Universal Tag Readouts

Locus 2 Specific Sequence

cTag2 sequenceTag2 sequence

SubstrateBead or Chip

C T A G

Multiplex ~1,000 SNPs

Not dependent on primary PCRIllumina

ParAllele

Affymetrics

Illumina Platform

96 Multi-array Matrix matches standard microtiter plates~ 1,500 SNPs typed per matrix for 96 samples

Affymetrix’s 100K Chip

http://www.affymetrix.com/products/arrays/specific/100k.affx

Optimized for 250-2000bp

High Throughput Chip Formats

Defining the scale of the genotyping project is key to selecting an approach:

5 to 10 SNPs in a candidate gene - Many approaches (expensive ~ 0.60 per SNP/genotype)

48 ( to 96) SNPs in a handful of candidate genes (~ 0.25 per SNP/genotype)

384 0 1,536 SNPs (~0.15 - 0.08 per SNP/genotype)

10,000 cSNPs - defined format(~0.05 per SNP/genotype)

100,000 Genic SNPs - defined format(~0.005 per SNP/genotype

500,000 SNPs defined format(~0.004 per SNP/ genotype)

1000 individuals

$6,000

$12,000

$57,600-122,880

$500,000

$500,000

$2,000,000

AcknowledgementsAcknowledgements

Allan Rettie, Medicinal ChemistryAllan Rettie, Medicinal ChemistryAlex ReinerAlex ReinerDave VeenstraDave VeenstraDave BloughDave BloughKen ThummelKen Thummel

Noel HastingsNoel HastingsMaggie AhearnMaggie Ahearn

Josh SmithJosh SmithChris BaierChris BaierPeggy Dyer-RobertsonPeggy Dyer-Robertson

Washington UniversityWashington UniversityBrian GageBrian GageHoward McLeodHoward McLeodCharles EbyCharles Eby

Joyce You - Hong KongJoyce You - Hong Kong

Documents

SNP Discovery and Analysis: Application to Association Studies Mark J. Rieder, PhD Dana Crawford, PhD Deborah Nickerson, PhD SeattleSNPs PGA July 19-20,