Stata%20commands%20for%20moving%20data%20between%20PHASE%20and%20HaploView%20Stata%20Conference%20DC%20

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Stata commands for moving data between PHASE and
HaploViewStata Conference DC 09July 30-31,
2009

• John Charles Chuck Huber Jr, PhD
• Assistant Professor of Biostatistics
• Department of Epidemiology and Biostatistics
• School of Rural Public Health
• Texas AM Health Science Center
• jchuber_at_tamu.edu

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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
• Write new Stata commands that do the same
  analyses
• Write Stata commands that efficiently export and
  import data for these boutique programs

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Stata for Genetic Data Analysis

• Outline
• Genetic Data Analysis using Stata
• Genetics Background
• The file commands in Stata
• The phasein and phaseout commands
• The HaploView program
• The haploviewout command
• Summary

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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,
  HardyWeinberg equilibrium, calculating and
  plotting linkage disequilibrium, estimating
  haplotypes, and interfacing with external
  programs.

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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.

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User Written Genetics Commands

• 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

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User Written Genetics Commands

• 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.

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The Post-Genome Era
February 16, 2001
February 15, 2001
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Scientific Method Observe
Hartl Jones (1998) pg 18, Figure 1.13
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Scientific Method Predict
Watson et al. (2004) pg 29, Box 2-2
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Scientific Method Manipulate
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The Structure of DNA
Hartl Jones (1998) pg 9, Figure 1.5
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The Structure of DNA
Watson et al. (2004) pg 23, Figure 2.5
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What is a SNP?

• A SNP is a single nucleotide polymorphism (the
  individual nucleotides are called alleles)
• ataagtcgatactgatgcat
  agctagctgactgacgcgat ataagtccatactgatgcat
  agctagctgactgaagcgat
• ataagtccatactgatgcatagctagctgactgacgcgat
• ataagtcgatactgatgcatagctagctgactgaagcgat

Person 1 Chromosome 1
Person 1 Chromosome 2
Person 2 Chromosome 1
Person 2 Chromosome 2
SNP1
SNP2
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Allelic Association

• Simple 2x2 table
• One table per SNP
• Compute a simple chi-squared statistic or odds
  ratio for each SNP

SNP1 Allele SNP1 Allele
g c
Case 250 750
Control 650 350
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Genotypic Association

• Compute chi-squared tests
• Allows testing of various disease models
  (dominant, recessive, additivity)

SNP1 Genotype SNP1 Genotype SNP1 Genotype
gg gc cc
Case 100 250 150
Control 300 150 50
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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
• ataagtcgatactgatgcat
  agctagctgactgacgcgat ataagtccatactgatgcat
  agctagctgactgaagcgat
• ataagtccatactgatgcatagctagctgactgacgcgat
• ataagtcgatactgatgcatagctagctgactgaagcgat

Person 1 Chromosome 1
Person 1 Chromosome 2
Person 2 Chromosome 1
Person 2 Chromosome 2
SNP1
SNP2
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Haplotypic Association

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

SNP1SNP2 Haplotype SNP1SNP2 Haplotype SNP1SNP2 Haplotype SNP1SNP2 Haplotype
ac at gc gt
Case 100 250 75 75
Control 300 100 50 50
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Why are haplotypes important?
2009 Oxford and Cambridge Boat Race
http//www.theboatrace.org/gallery/2009?page7
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Why are haplotypes important?
SNP1
SNP2
SNP3
SNP4
SNP5
Chromosome R
Chromosome D
President
VP
State
Defense
Treasury
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Why are haplotypes important?
SNP1
SNP2
SNP3
SNP4
SNP5
Chromosome R
Chromosome D
President
VP
State
Defense
Treasury
Rearranging the members of each chromosome
could have a profound effect!
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Why are haplotypes important?
Hartl Jones (1998) pg 18, Figure 1.13
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Hartl Jones (1998) pg 18, Figure 1.13
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Why are haplotypes important?
Watson et al. (2004) pg 29, Box 2-2
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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)

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The phaseout Command
Raw Genotype Data in Stata
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The phaseout Command
Input file format for PHASE
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The phaseout Command
I need to get my data from here
to here
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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

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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?

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The phaseout Command

• Syntax for phaseout
• phaseout SNPlist , idvariable(string)
  filename(string) missing(string)
  separator(string) positions(string)
• Example
• local SNPList "rs1413711 rs3024987 rs3024989"
• local PositionsList "674 836 1955
• phaseout SNPList' , idvariable("id")
  filename("VEGF.inp") missing("X/X 9/9")
  positions(PositionsList') separator("/")

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The phaseout Command

• Example
• local SNPList "rs1413711 rs3024987 rs3024989"
• local PositionsList "674 836 1955
• phaseout SNPList' , idvariable("id")
  filename("VEGF.inp") missing("X/X 9/9")
  positions(PositionsList') separator("/")

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The phaseout Command

• Example
• local SNPList "rs1413711 rs3024987 rs3024989"
• local PositionsList "674 836 1955
• phaseout SNPList' , idvariable("id")
  filename("VEGF.inp") missing("X/X 9/9")
  positions(PositionsList') separator("/")

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The phasein Command

• Syntax for phasein
• phasein PhaseOutputFile , markers(string)
  positions(string)
• Example
• phasein VEGF.out, markers("MarkerList.txt")
  positions("PositionList.txt")

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The phasein Command
Output file format from PHASE
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The phasein Command

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

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The phasein Command

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

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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)

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The haploviewout Command

• Syntax for haploviewout
• haploviewout SNPlist , idvariable(string)
  filename(string) positions(string)
  familyid(string) poslabel
• Example
• local MarkerList "rs1413711 rs3024987 rs3024989
• haploviewout MarkerList', idvariable(id)
  filename("VEGF") poslabel

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The haploviewout Command

• Example
• local SNPList "rs1413711 rs3024987 rs3024989
• haploviewout MarkerList', idvariable(id)
  filename("VEGF") poslabel

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The haploviewout Command

• Example
• local SNPList "rs1413711 rs3024987 rs3024989
• haploviewout MarkerList', idvariable(id)
  filename("VEGF") poslabel

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The haploviewout Command
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The haploviewout Command
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The haploviewout Command
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Summary

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

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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 AM College of
  Veterinary Medicine
• Roger Newson of the Imperial College London

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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, 11621169.
• Stephens, M., Smith, N. J., Donnelly, P.
  (2001). A New Statistical Method for Haplotype
  Reconstruction from Population Data. American
  Journal of Human Genetics, 68, 978989.
• 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