Final Biology Group Presentation

December 9-11, 2009Biophysics 101

Anugraha Raman, Jacqueline Nkuebe and Ridhi Tariyal

Trait-o-matic Phenotype

MODEL

LIT

MODEL

Phenotype

GWAS Data Proposal to the Rotterdam Management Team

Creation of Test Data with the Modeling Team

Correspondence with various scientists to begin to create a sane model for gene-gene interactions

Hypothesis-building tool

SNP query tool

Overview

• Recap from Eye Color Presentation of 11/24• Thinking of How Everything Fits Together:– Thought-projects realized by the Infrastructure Team– Working with the Modeling Group– Dataset Creation

• Future Directions

Just a recap from last time….

WHO?

• Target Consumer: – High school student with mathematical skills,

discretionary time and a keen sense of curiosity OR– Biologists with very specific, high end needsOR– Experimental geneticistsOR– Clinical geneticists

Let’s think about how everything fits together…

• To make edit/add features to Trait-o-Matic based on our bio-stream research – Research Friendly– Increased Utility

Goal 1

Querying for SNPs by Chromosomal Location

“We realized that it would be helpful to be able to type in a particular SNP location and get a listing of all of the genotypes for that location for everyone in the Trait-o-matic database…”

SNP specific Data by Allele/Trait+ + - - - + +

SNP_1 SNP_2 SNP_3 SNP_4 SNP_5 SNP_6 SNP_7CV

CHF MAF MAF MAF MAFAtheroscleorsis

Metabolic DiseasesDiabetesObesity

NSAZMS

GET ME DATA FOR THESE ALLELES

Goal 2

• Provide test case details: We decided that thinking about LD (linkage-disequilibrium) in a math model was ultimately unnecessary…• Complicate problem too much• This can be a future direction once basic

models are in place

Where do we find this new dataset?

Dataset Creation (“Toy” Story)

HapMap data? (HaploView)

Discussion with the Math Modeling Group about an

ideal dataset

Rotterdam Study Correspondence (and others) (Dr.

Liu)—Wrote a proposal to the

Management Team

The Process

Literature Search Yielded…

SNP-ID Chr Position Gene Allele

rs16891982 5 33987450 SLC45A2(MATP) CG

rs26722 rs12203592 rs1408799 5 6 9 33999627 341321 12662097 SLC45A2(MATP) IRF4 TYRP1 CT CT CT

rs683 9 12699305 TYRP1 AC

rs1393350 11 88650694 TYR AG

rs12896399 14 91843416 SLC24A4 GT

rs2594935 15 25858633 OCA2 AG

rs728405 15 25873448 OCA2 AC

rs1800407 15 25903913 OCA2 CT

rs3794604 15 25945660 OCA2 CT

rs4778232 15 25955360 OCA2 CT

rs1448485 15 25956336 OCA2 GT

rs8024968 15 25957284 OCA2 CT

rs1597196 15 25968517 OCA2 GT

rs7179994 15 25997365 OCA2 AG

rs4778138 15 26009415 OCA2 AG

rs4778241 15 26012308 OCA2 AC

SNP-ID Chr Position Gene Allele

rs7495174 15 26017833 OCA2 AG

rs1129038 rs12593929 15 15 26030454 26032853 HERC2 HERC2 CT AG

rs12913832 15 26039213 HERC2 AG

rs7183877 15 26039328 HERC2 AC

rs3935591 15 26047607 HERC2 CT

rs7170852 15 26101581 HERC2 AT

rs8041209 15 26117253 HERC2 GT

rs8028689 15 26162483 HERC2 CT

rs2240203 15 26167797 HERC2 CT

rs2240202 15 26184490 HERC2 AG

rs916977 15 26186959 HERC2 CT

rs16950979 15 26194101 HERC2 AG

rs2346050 15 26196279 HERC2 CT

rs16950987 15 26199823 HERC2 AG

rs1667394 15 26203777 HERC2 CT

rs12592730 15 26203954 HERC2 AG

rs1635168 15 26208861 HERC2 AC

rs6058017 20 32320659 ASIP AG

~34 Eye-Color SNPs

Combining Biological and Modeling Group Requirements

1. Read a CSV(i.e. spreadsheet on excel) file of SNP/phenotype data and process it into python (it is general enough to deal with arbitrarily many SNPs and multiple phenotypes so long as they are ordinal (ie. as long as there are phenotypes we can call 0, 1, ...)).

2. Process these arrays into conditional probabilities.

3. Take logits of probabilities, make an array of these logits where each genotype maps to its corresponding probabilities.

4. Link into a scipy ols package, and perform a regression

5. Take in a new genotype and provide the predicted phenotype (probably using PGP 10 genotype inputs)

Enter HapMap

Chromosome 15 (Eye Color Specific Region)

What’s missing? Corresponding phenotypic data…

Data-Set Creation

1 2 3 4 5 6 7 8 9 10 11 12 Rule 1 Phenotype 1 Rule 2 Phenotype 2AT TT CG GG CG GG CG GG AT TT AT TT AT TT CG GG CG GG CG GG AT TT AT TT

1 0 1 1 0 1 1 1 1 0 0 1 1 1 0 1 1 0 1 0 1 1 0 0 1 6 intermediate 2.17 blue2 1 1 0 1 0 1 0 1 1 0 0 1 0 0 0 0 0 1 1 1 1 0 1 0 15 brown 1.5 blue3 0 1 0 1 0 1 1 0 1 0 0 0 1 1 1 0 1 0 1 0 1 1 1 1 15 brown 9.4 intermediate4 0 1 0 0 0 1 1 1 1 0 0 1 1 0 0 1 1 1 1 0 0 0 1 0 15 brown 5.5 intermediate5 1 0 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 0 1 1 0 0 15 brown 6.57 intermediate6 0 0 1 1 1 0 0 1 1 1 1 1 0 0 1 0 0 0 0 0 0 1 1 1 3 blue 2.57 blue7 0 0 0 1 1 1 1 0 1 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 17 brown 5.4 intermediate8 1 0 0 1 0 1 1 1 1 0 1 0 0 1 1 0 0 1 1 0 0 0 0 0 17 brown 6.5 intermediate9 1 1 0 0 1 0 0 1 0 1 0 0 1 0 1 1 1 0 1 1 1 0 1 0 13 brown 5.5 intermediate

10 0 0 1 0 1 0 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 0 0 0 3 blue 9.67 intermediate11 0 1 1 0 0 1 1 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 18 brown 4.67 blue12 1 0 1 1 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 1 0 0 1 0 3 blue 0.67 blue13 0 1 1 0 0 0 0 1 1 1 0 1 1 0 1 1 0 1 0 0 0 1 0 1 1 blue 2.57 blue14 1 1 1 0 0 1 0 0 1 1 1 0 1 0 1 0 1 0 0 0 1 1 0 0 6 intermediate 5.07 intermediate15 0 1 1 1 1 1 0 1 1 1 1 0 0 1 1 1 0 1 1 1 1 0 1 1 18 brown 7.17 intermediate16 0 1 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 1 0 0 1 1 0 0 6 intermediate 5.4 intermediate17 1 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 1 1 1 1 0 blue 6.57 intermediate18 1 0 0 0 1 1 0 1 0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 0 5 intermediate 1.9 blue19 1 1 1 0 1 1 0 1 1 0 1 0 1 0 1 0 1 1 1 1 1 1 0 1 18 brown 6.57 intermediate20 0 1 0 0 0 1 0 0 0 1 0 0 1 0 0 1 1 1 0 1 0 0 0 0 3 blue 4 blue21 0 1 1 0 1 0 1 0 0 0 1 1 0 1 1 0 0 0 1 0 0 0 0 0 16 brown 5.67 intermediate22 1 0 0 0 1 0 1 0 0 1 1 1 1 1 1 0 0 1 1 0 1 1 0 1 15 brown 5.4 intermediate23 0 0 1 1 0 0 0 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 3 blue 2.17 blue24 1 0 0 0 1 1 0 0 0 0 1 0 1 0 0 0 1 1 0 0 1 1 0 0 5 intermediate 4.4 blue25 0 1 1 1 0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 1 1 0 1 0 4 blue 7.17 intermediate

1 2 3 4 5 6 7 8 9 10 11 12 Rule 1 Phenotype 1 Rule 2 Phenotype 2AT TT CG GG CG GG CG GG AT TT AT TT AT TT CG GG CG GG CG GG AT TT AT TT

1 1 1 0 0 0 0 1 0 1 0 1 0 1 0 1 0 1 1 0 0 1 1 1 0 4 blue 4.4 blue2 1 0 0 1 1 0 0 0 1 1 1 1 0 0 1 0 0 1 0 1 1 0 1 0 3 blue 0 blue3 1 0 0 0 0 1 1 0 1 0 1 0 0 1 0 1 1 1 0 1 1 0 1 1 5 intermediate 9 intermediate4 1 1 1 1 0 1 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 0 1 0 6 intermediate 9.67 intermediate5 0 1 0 0 0 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 0 1 1 4 blue 6.5 intermediate6 1 1 0 0 0 0 1 1 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 1 1 blue 5.9 intermediate7 0 0 1 0 0 1 0 1 1 1 1 0 0 0 1 0 0 0 0 1 1 0 0 1 5 intermediate 2.17 blue8 0 1 1 0 0 1 0 1 1 1 0 0 1 0 0 0 1 1 1 0 0 0 0 1 15 brown 6.17 intermediate9 1 1 0 1 1 1 0 1 0 1 0 1 0 0 0 1 1 0 0 0 0 1 1 0 3 blue 5.9 intermediate

10 1 0 0 0 0 1 0 1 0 0 1 0 0 0 0 1 1 0 1 0 0 0 1 1 17 brown 5.5 intermediate11 0 0 0 1 1 1 0 1 1 0 1 1 1 1 1 0 0 1 1 1 0 1 0 0 17 brown 6.9 intermediate12 0 1 1 0 0 0 1 1 0 1 1 0 1 0 1 1 1 1 0 1 0 0 1 1 4 blue 6.17 intermediate13 0 0 1 1 1 1 1 1 1 1 1 0 1 0 0 0 0 1 1 1 1 1 0 0 17 brown 2.57 blue14 1 0 1 0 1 1 1 0 0 0 1 1 1 1 1 0 1 0 0 1 1 1 0 0 5 intermediate 10.07 intermediate15 1 1 0 1 0 1 1 1 0 0 1 0 1 1 0 1 0 1 0 1 1 0 1 0 6 intermediate 6.5 intermediate16 0 1 1 1 1 1 1 1 1 0 1 1 0 1 0 1 0 1 0 1 0 1 1 1 6 intermediate 7.57 intermediate17 1 1 0 0 1 1 1 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 6 intermediate 0 blue18 1 0 0 1 1 0 0 1 0 1 0 0 1 1 1 0 1 0 0 1 0 1 0 0 0 blue 10.9 intermediate19 1 0 0 0 0 0 1 0 0 0 1 0 1 1 1 1 0 0 0 0 1 1 1 0 3 blue 5.4 intermediate20 0 1 1 1 1 0 1 1 0 1 1 1 0 1 0 1 0 1 1 0 1 1 1 0 16 brown 7.57 intermediate21 0 0 0 1 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 1 0 1 0 1 15 brown 5.4 intermediate22 1 0 0 1 1 1 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 17 brown 5 intermediate23 1 0 1 0 1 1 0 0 0 1 1 1 1 1 1 0 0 1 0 1 0 0 1 1 5 intermediate 5.67 intermediate24 1 1 1 0 1 1 0 0 1 1 1 0 0 0 0 1 1 1 0 0 1 1 0 1 6 intermediate 5.07 intermediate25 1 0 1 0 0 1 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 5 intermediate 7.17 intermediate

Phenotypic Ranges:(0-4)= Blue (5-12)= Intermediate (13-19)= Brown

Rules:(.5*homozygous recessive SNP1 + 2*homozygous recessive SNP3+ 3*heterozygous SNP6+ 12*heterozygous SNP10)

(.67*heterozygous SNP2+ 1.5*homozygous recessive SNP4+ 5*homozygous recessive SNP7+ 4*heterozygous SNP9+ .4*homozygous recessive SNP11)

1 2 3 4 5 6 7 8 9 10 11 12 Rule 1 Phenotype 1 Rule 2 Phenotype 2AT TT CG GG CG GG CG GG AT TT AT TT AT TT CG GG CG GG CG GG AT TT AT TT

1 1 1 0 1 1 1 1 1 1 0 0 0 0 1 1 0 1 0 1 1 0 1 1 1 15 brown 10.9 intermediate2 1 1 0 0 1 0 0 1 0 1 0 1 0 0 1 0 1 1 0 1 0 1 1 1 1 blue 5.9 intermediate3 1 0 0 1 0 1 0 1 1 1 0 0 1 0 1 1 1 1 0 1 1 1 1 1 2 blue 5.9 intermediate4 1 1 0 1 1 1 1 1 0 1 0 0 1 1 1 0 1 1 0 0 1 1 1 1 3 blue 10.9 intermediate5 0 0 1 0 0 1 1 1 1 1 1 0 1 1 1 1 0 1 0 1 1 0 1 1 5 intermediate 7.17 intermediate6 1 0 1 0 1 0 1 0 1 1 1 0 1 1 0 1 0 0 1 0 0 1 0 1 15 brown 6.07 intermediate7 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 1 1 0 1 12 brown 4.4 blue8 0 0 1 1 1 0 0 1 1 0 1 0 1 0 1 0 0 1 1 1 1 0 0 1 15 brown 2.17 blue9 0 0 1 1 0 0 1 0 1 0 0 0 1 0 0 1 0 0 0 1 1 1 1 1 0 blue 1.07 blue

10 0 0 0 1 1 0 0 0 1 0 1 1 1 1 1 0 0 0 0 1 0 1 0 0 3 blue 5.4 intermediate11 1 1 0 0 1 1 0 1 1 0 0 0 1 1 0 1 1 1 1 1 1 1 0 1 15 brown 10.9 intermediate12 0 0 0 0 0 1 0 0 1 0 1 0 0 1 1 0 1 0 0 0 0 0 1 0 5 intermediate 9 intermediate13 1 0 0 0 1 1 1 1 1 1 1 0 1 0 1 1 0 0 0 1 0 0 1 1 5 intermediate 1.5 blue14 1 0 1 0 0 0 0 1 0 1 1 0 1 0 1 1 0 1 1 0 0 1 0 0 15 brown 2.57 blue15 1 1 0 1 0 0 0 1 1 1 1 1 1 1 0 0 1 1 1 0 1 0 1 0 16 brown 10.5 intermediate16 0 1 0 1 0 1 1 0 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 6 intermediate 5 intermediate17 1 1 1 1 0 1 1 0 0 0 1 1 0 1 1 0 1 0 0 1 0 0 0 1 6 intermediate 9.67 intermediate18 1 0 1 0 1 1 0 0 1 1 0 0 0 1 1 1 1 0 0 1 1 0 0 1 2 blue 9.67 intermediate19 1 1 1 0 1 1 1 1 1 0 0 0 0 1 0 0 1 1 0 1 0 0 1 0 3 blue 11.17 intermediate20 0 0 1 0 0 0 0 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 1 15 brown 11.57 intermediate21 1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 1 0 1 15 brown 5.4 intermediate22 0 0 1 1 1 0 0 1 0 0 1 0 0 0 0 1 1 0 0 0 1 0 1 1 3 blue 6.17 intermediate23 1 1 0 1 1 0 0 0 0 1 0 0 1 1 0 1 0 0 1 1 0 0 1 0 13 brown 5 intermediate24 0 0 0 1 1 0 1 0 1 0 0 1 1 0 0 0 0 0 0 0 1 1 0 0 0 blue 0.4 blue25 1 0 0 0 1 0 1 0 1 0 1 0 0 1 1 0 1 1 1 1 0 0 1 1 15 brown 9 intermediate

Future Directions

Finding info for Future Trait Investigations

Now, since we can download HapMap based data from dbSNP, this population diversity info can be thoroughly evaluated in future tools

Factoring in Environmental Factors• Way to combine human phenome project,

environmental knowledge, genotype and Trait-o-Matic in a consistent, usable way

SNP_1 SNP_2 SNP_6 SNP_7 CHFMedicine

Family History Diet

Exposure to Carcinogens Ethnicity

Location of Primary Residence

George Church A A T T NOHarris Wang A A T T NOCraig Venter A A T T NOSasha P A A T T NOX T T A A YESY T T A A YESZ T T A A YES

Protein-Protein Interactions• If goal is to truly model epistasis, you need to understand all

protein-protein interactions

Gene, Chromosome Function of Protein Product Involved in the the Following Metabolic Pathways Predicted Interacting Partners (Protein ID)

SNP_1

SNP_2

SNP_3

SNP_4

• Above we see a matrix for protein products of these genes. Sometimes we have to look at surrounding protein interactions as well (ABO Blood Typing)• Bombay Phenotype makes phenotypic determination of offspring

difficult• If the recessive form of H antigen (found on surface of rbcs) is

inherited from two parents a child can have blood type O even if both parents do not have O.

• H antigen is precursor to A and B antigens in blood

Future Directions• Tutorial on how to use Trait-o-Matic add-ons• SNP location based query tool

• 3-D visualization (student appeal)• click on a different portions a human body

to look at traits associated with that particular area

• Potential Forensics Application (expanding target audience)• Choose list of traits known in suspect

creation of potential DNA sequence/ Image

And More…

• Exploring the question of chromosomal location standardization (Bruce Birren)– in progress

• Improving collection of phenotype data from PGP participants – what does the current questionnaire look like?

• Organization of phenotype-outputs in T-O-M• Pharmaco-genetics Direction

Final Progress and Contributions

THANKS!

• Professor Church and Harris • Sasha• Dr. Fan Liu and Manfred Kayser (Rotterdam)• Dr. Bruce Birren, Amy Carmargo (Broad)• Biophysics 101 (’09)