GEIRA: Gene-Environment and Gene-Gene Interaction Research
Application
R version 1.0
User’s manual
Henrik Källberg
Institute of Environmental Medicine
Karolinska Institutet
171 77 Stockholm, Sweden
June 1, 2010
Freely download at:
URL http://www.epinet.se
GEIRAD Gene Environmental Interaction Research Application
Dominant model
Description
This is an application for automatically calculating interaction effects on extensive
genome-wide or dense gene data. The application could be used to calculate geneenvironment or gene-gene interaction. Both additative interaction and multiplicative
interaction is calculated and options for the dominant genetic model. Attributable
proportion due to interaction is calculated as a measure of additative interaction. The
underlying measure is the odds ratios which are calculated through general linear
models with a logistic link function.
Usage
GEIRAD(dname, dname2, dname3, start, stop, covar, envi, FILE, id)
Arguments
dname
define where the tped data file containing snp information is
available, the name of it and the format of the file (tped.txt-file).
dname2
define where the tfam data file containing disease and id
information is available, the name of it and the format of the file
(tfam-file).
dname3
define where the data file containing covariate and environmental
factor information is available, the name of it and the format of the
file (tfam-file).
start
state where the first column(variable) for starting the calculations.
stop
state how many variables from the end that should be rejected (not
included in the calculations)
covar
define name of the covariate.
envi
define name of the interaction variable.
FILE
define where the output data file and the name of it will be placed
id
define the name of the id variable.
Details
It is important to follow the same order for the data sets in the function. If not the same
order is used wrong data set will be used for the calculations and will result in error
message.
Value
chr
What chromosome the snp belong to.
snp
The rs number of the snp.
ORii
The odds ratio for the combination of risk allele and the envi
factor.
ORiiL
The lower limit for the 95% confidence limit regarding the odds
ratio for the combination of risk allele and the envi factor.
ORiiH
The upper limit for the 95% confidence limit regarding the odds
ratio for the combination of risk allele and the envi factor.
ORio
The odds ratio for the envi factor by itself.
ORioL
The lower limit for the 95% confidence limit regarding the odds
ratio for the envi factor by itself.
ORioH
The upper limit for the 95% confidence limit regarding the odds
ratio for the envi factor by itself.
ORoi
The odds ratio for the risk allele by itself.
ORoiL
The lower limit for the 95% confidence limit regarding the odds
ratio for the risk allele by itself.
ORoiH
The upper limit for the 95% confidence limit regarding the odds
ratio for the risk allele by itself.
AP
The attributable proportion due to interaction
AP.low
The lower limit for the 95% confidence limit regarding the
attributable proportion due to interaction
AP.high
The upper limit for the 95% confidence limit regarding the
attributable proportion due to interaction
AP.p
The p-value for the attributable proportion due to interaction.
Mult
p-value for multiplicative interaction coefficient.
Ind10_1
Number of cases with risk allele and no envi exposure.
Ind10_0
Number of controls with risk allele and no envi exposure.
Ind01_1
Number of cases with envi exposure and no risk allele.
Ind01_0
Ind11_1
Number of controls with envi exposure and no risk allele.
Number of cases with envi exposure and two risk alleles.
Ind11_0
Number of controls with envi exposure and two risk alleles.
minor
minor allele.
major
major allele.
risk
risk allele.
cc_minor
minor allele frequency.
cc_major
major allele frequency
cc_minor_ctrl
minor allele frequency controls.
cc_minor_case
minor allele frequency cases.
cc_major_ctrl
major allele frequency controls.
cc_major_case
major allele frequency cases.
References
Cardon, L.R. and Bell, J.I. (2001) Association study designs for complex diseases, Nat Rev
Genet, 2, 91-99.
Moore, J.H. (2003) The ubiquitous nature of epistasis in determining susceptibility to
common human diseases, Hum Hered, 56, 73-82.
Plenge, R.M., Seielstad, M., Padyukov, L., Lee, A.T., Remmers, E.F., Ding, B., Liew, A.,
Khalili, H., Chandrasekaran, A., Davies, L.R., Li, W., Tan, A.K., Bonnard, C., Ong, R.T.,
Thalamuthu, A., Pettersson, S., Liu, C., Tian, C., Chen, W.V., Carulli, J.P., Beckman, E.M.,
Altshuler, D., Alfredsson, L., Criswell, L.A., Amos, C.I., Seldin, M.F., Kastner, D.L.,
Klareskog, L. and Gregersen, P.K. (2007) TRAF1-C5 as a risk locus for rheumatoid arthritis-a genomewide study, N Engl J Med, 357, 1199-1209.
Purcell, S. et al. (2007) PLINK: A Tool Set for Whole-Genome Association and PopulationBased Linkage Analyses, Am J Hum Genet, 81, 559-575.
Rothman, K.J. (2002) Epidemiology. An introduction. Oxford University Press, New York.
Sing, C.F. et al. (2004) Dynamic relationships between the genome and exposures to
environments as causes of common human diseases, World Rev Nutr Diet, 93, 77-91.
Thornton-Wells, T.A. et al. (2004) Genetics, statistics and human disease: analytical retooling
for complexity, Trends Genet, 20, 640-647.
Källberg H, Ahlbom A, Alfredsson L. Eur J Epidemiol. 2006;21(8):571-3. Epub 2006 Sep 13.
Calculating measures of biological interaction using R.
Example
Basic function without specification of data sets and variables:
GEGEID(dname,dname2,dname3,start,stop,covar,envi,FILE,id)
Function for running the sample dataset if the data sets are located on a directory called R
under program located on the local hard drive c:
GEGEID("c:/program/R/samples.tped","C:/Program/R/sample.tfam","C:/Program/R/SampleC
ov.txt",1,0,covar="cov",envi="env",FILE="c:/program/R/wgi2.r",id="indid")