Stata commands for moving data between PHASE and HaploView Stata Conference DC ‘09 July 30-31, 2009 John Charles “Chuck” Huber Jr, PhD Assistant Professor.

Stata commands for moving data between PHASE and HaploView

Stata Conference DC ‘09July 30-31, 2009

John Charles “Chuck” Huber Jr, PhDAssistant Professor of Biostatistics

Department of Epidemiology and BiostatisticsSchool of Rural Public Health

Texas A&M Health Science [email protected]

Motivation

Many rapidly growing areas of research utilize multiple specialty “boutique” computer programs to conduct highly specialized analyses.

The Stata user is faced with two choices:1. Write new Stata commands that do the same analyses2. Write Stata commands that efficiently export and import data for these

“boutique” programs

Stata for Genetic Data Analysis

Outline

1. Genetic Data Analysis using Stata2. Genetics Background3. The “file” commands in Stata4. The phasein and phaseout commands5. The HaploView program6. The haploviewout command7. Summary

Stata for Genetic Data Analysis

2007 UK Stata Users Group meeting:http://www.stata.com/meeting/13uk/

A brief introduction to genetic epidemiology using Stata Neil Shephard, University of Sheffield

An overview of using Stata to perform candidate gene association analysis will be presented. Areas covered will include data manipulation, Hardy–Weinberg equilibrium, calculating and plotting linkage disequilibrium, estimating haplotypes, and interfacing with external programs.

http://www.stata.com/meeting/13uk/

User Written Genetics Commands

Programs written by David Clayton• ginsheet- Read genotype data from text files.• gloci - Make a list of loci.• greshape - Reshape a file containing genotypes to a file of alleles.• gtab - Tabulate allele frequencies within genotypes and generate indicators (performs Hardy-Weinberg

Equilibrium testing).• gtype - Create a single genotype variable from two allele variables.• htype - Create a haplotype variable from allele variables.• mltdt - Multiple locus TDT for haplotype tagging SNPs (htSNPs).• origin - Analysis of parental origin effect in TDT trios.• pseudocc - Create a pseudo-case-control study from case-parent trios.• pscc - Experimental version of pseudocc in which there may be several groups of linked loci.• pwld - Pairwise linkage disequilibrium measures.• rclogit - Conditional logistic regression with robust standard errors.• snp2hap - Infer haplotypes of 2-locus SNP markers.• tdt - Classical TDT test.• trios - Tabulate genotypes of parent-offspring trios.


Programs written by Adrian Mander• gipf - Graphical representation of log-linear models.• hapipf - Haplotype frequency estimation using an EM algorithm and log-linear modelling.• pedread - Read's pedigree data file (in pre-Makeped LINKAGE format), similar to ginsheet• pedsumm - Summarises a pre-Makeped LINKAGE file that is currently in Stata's memory.• pedraw - Draws one pedigree in the graphics window• plotmatrix - Produces LD heatmaps displaying graphically the strength of LD between markers.• profhap - Calculates profile likelihood confidence intervals for results from hapipf• swblock - A step-wise hapipf routine to identify the parsimonious model to describe the Haplotype block

pattern.• qhapipf - Analysis of quantitative traits using regression and log-linear modelling when phase is unknown.• hapblock - attempts to find the edge of areas containing high LD within a set of loci


Programs written by Mario Cleves• gencc - Genetic case-control tests• genhw - Hardy-Weinberg Equilibrium tests• qtlsnp - A program for testng associations between SNPs an a quantitative trait.

Programs written by Catherine Saunders• co_power - Power calculations for Case-only study designs.• gei_matching - • geipower - Power calculations for Gene-Environment interactions.• ggipower - Power calculations for Gene-Gene interactions.• tdt_geipower - Power calculations for Gene-Environment interactions via TDT analysis.• tdt_ggipower - Power calculations for Gene-Gene interactions via TDT analysis.

Programs written by Neil Shephard• genass- Performs a number of statistical tests on your genotypic data and collates the results into a Stata

formatted data set for browsing.

The Post-Genome Era

February 16, 2001February 15, 2001

Scientific Method: Observe

Hartl & Jones (1998) pg 18, Figure 1.13

Scientific Method: Predict

Watson et al. (2004) pg 29, Box 2-2

Scientific Method: Manipulate

The Structure of DNA


The Structure of DNA

Watson et al. (2004) pg 23, Figure 2.5

What is a SNP?

• A SNP is a single nucleotide polymorphism (the individual nucleotides are called alleles)

ataagtcgatactgatgcatagctagctgactgacgcgat ataagtccatactgatgcatagctagctgactgaagcgat

ataagtccatactgatgcatagctagctgactgacgcgat

ataagtcgatactgatgcatagctagctgactgaagcgatSNP1 SNP2

Person 1 – Chromosome 1 Person 1 – Chromosome 2


Allelic Association• Simple 2x2 table• One table per SNP• Compute a simple chi-squared statistic or odds

ratio for each SNP

SNP1 Allele

g c

Case 250 750

Control 650 350

Genotypic Association

• Compute chi-squared tests • Allows testing of various disease models

(dominant, recessive, additivity)

SNP1 Genotype

gg gc cc

Case 100 250 150

Control 300 150 50

What is a Haplotype?

• A haplotype is the combination of one or more alleles found on the same chromosome– Person 1 has a “gc” haplotype and a “ca” haplotype– Person 2 has a “cc” haplotype and a “ga” haplotype

ataagtcgatactgatgcatagctagctgactgacgcgat ataagtccatactgatgcatagctagctgactgaagcgat

ataagtccatactgatgcatagctagctgactgacgcgat

ataagtcgatactgatgcatagctagctgactgaagcgatSNP1 SNP2



Haplotypic Association

• Compute chi-squared tests • Two SNPs with genotypes a/g and c/t respectively

SNP1:SNP2 Haplotype

a:c a:t g:c g:t

Case 100 250 75 75

Control 300 100 50 50

Why are haplotypes important?

http://www.theboatrace.org/gallery/2009?page=7#

2009 Oxford and Cambridge Boat Race


Chromosome R

Chromosome D

President VP State Defense Treasury

SNP1 SNP2 SNP3 SNP4 SNP5


Chromosome R

Chromosome D

President VP State Defense Treasury

SNP1 SNP2 SNP3 SNP4 SNP5

Rearranging the members of each “chromosome” could have a profound effect!





Watson et al. (2004) pg 29, Box 2-2

The PHASE Program

• Unfortunately, haplotypes are not observed directly using modern, high-throughput lab techniques

• We observe genotypes and must infer the haplotype structure using algorithms

• PHASE is a very popular program for inferring haplotypes from many SNPs simultaneously (Stephens, Smith & Donnelly, 2001)

The phaseout Command

Raw Genotype Data in Stata


Input file format for PHASE


I need to get my data from here:

to here:

The “file” commands in Stata

Using “file open”, “file write” and “file close”

file open Example1 using "ExampleFile.txt", write replace

file write Example1 "Hello World" _newline(1)

file write Example1 "Why so blue?" _newline(1)

file close Example1

The “file” commands in Stata

Using “file open”, “file read” and “file close”

. file open Example2 using "ExampleFile.txt", read

. file read Example2 Line1

. file read Example2 Line2

. file close Example2

. disp "Line1: `Line1'"

Line1: Hello World

. disp "Line2: `Line2'"

Line2: Why so blue?


Syntax for phaseout

phaseout SNPlist , idvariable(string) filename(string) [missing(string) separator(string) positions(string)]

Examplelocal SNPList "rs1413711 rs3024987 rs3024989"

local PositionsList "674 836 1955“

phaseout `SNPList' , idvariable("id") filename("VEGF.inp") missing("X/X 9/9") positions(`PositionsList') separator("/")

The phaseout CommandExamplelocal SNPList "rs1413711 rs3024987 rs3024989"



The phaseout CommandExamplelocal SNPList "rs1413711 rs3024987 rs3024989"



The phasein Command

Syntax for phasein

phasein PhaseOutputFile [, markers(string) positions(string)]

Example

phasein VEGF.out, markers("MarkerList.txt") positions("PositionList.txt")

The phasein Command

Output file format from PHASE

The phasein CommandExamplephasein VEGF.out, markers("MarkerList.txt")

positions("PositionList.txt")

The phasein CommandExamplephasein VEGF.out, markers("MarkerList.txt")

positions("PositionList.txt")

The HaploView Program

• Once we have inferred our haplotypes, we can conduct further association analyses using the full complement of Stata commands.

• We might also want to explore our data in the popular program HaploView (Barrett et al, 2005)

The haploviewout Command

Syntax for haploviewout

haploviewout SNPlist , idvariable(string) filename(string) [positions(string)] [familyid(string)] [poslabel]

Examplelocal MarkerList "rs1413711 rs3024987 rs3024989“

haploviewout `MarkerList', idvariable(id) filename("VEGF") poslabel

The haploviewout CommandExamplelocal SNPList "rs1413711 rs3024987 rs3024989“


The haploviewout CommandExamplelocal SNPList "rs1413711 rs3024987 rs3024989“





Summary

Compared to recreating “boutique” programs in Stata, it is relatively easy to create programs for exporting and importing data.

Acknowledgements

• Grant 1-R01DK073618-02 from the National Institute of Diabetes and Digestive and Kidney Diseases

• Grant 2006-35205-16715 from the United States Department of Agriculture.

• Drs. Loren Skow, Krista Fritz, Candice Brinkmeyer-Langford of the Texas A&M College of Veterinary Medicine

• Roger Newson of the Imperial College London

References• Barrett, J., Fry, B., Maller, J., & Daly, M. (2005). Haploview: analysis and

visualization of LD and haplotype maps. Bioinformatics, 21, 263-265.• Hartl, D.L., Jones, E.W. (1998) Genetics: Principles and Analysis, 4th Ed.

Jones & Bartlett Publishers• Stephens, M., & Donnelly, P. (2003). A Comparison of Bayesian Methods

for Haplotype Reconstruction from Population Genotype Data. American Journal of Human Genetics, 73, 1162–1169.

• Stephens, M., Smith, N. J., & Donnelly, P. (2001). A New Statistical Method for Haplotype Reconstruction from Population Data. American Journal of Human Genetics, 68, 978–989.

• Watson, J.D., Baker, T.A., Bell, S.P., Gann, A., Levine, M., Losick, R. (2004) Molecular Biology of the Gene, 5th Ed. Benjamin Cummings

Stata commands for moving data between PHASE and HaploView Stata Conference DC ‘09 July 30-31, 2009 John Charles “Chuck” Huber Jr, PhD Assistant Professor.

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