gene-environment, gene-gene interaction quanto (power calculation) hydrac/gxe
DESCRIPTION
Lab 3. Gene-Environment, Gene-Gene Interaction Quanto (power calculation) http://hydra.usc.edu/gxe/. Yu-Chun Jean Yen [email protected] Bldg.2 Rm. 200. Sample Dataset Yahoo06.dat: a comma delimited file Case-control with 1680 subjects, 16 SNPs. data yahoo; set yahoo; - PowerPoint PPT PresentationTRANSCRIPT
i. Gene-Environment, Gene-Gene Interactionii. Quanto (power calculation)
http://hydra.usc.edu/gxe/
Lab 3
Yu-Chun Jean [email protected] Rm. 200
Sample DatasetYahoo06.dat: a comma delimited file Case-control with 1680 subjects, 16 SNPs
data yahoo;
set yahoo;
/* define genotype scores for snps 5 and 10 */
z5=(a9 eq 3)+(a10 eq 3);
if a9 eq . or a10 eq . then z5=.;
z10=(a19 eq 4)+(a20 eq 4);
if a19 eq . or a20 eq . then z10=.;
run;
/* "interaction tests" assuming linear trend in log OR by SNP5 */
/* Get null -2 log L for "joint test" */
proc logistic data=yahoo;
where z5 ne . and x ne .; *complete case subset;
model d(event='2')=x;
/* Get null -2 log L for "test of statistical interaction" */
proc logistic data=yahoo;
where z5 ne . and x ne .;
model d(event='2')=x z5;
proc logistic data=yahoo;
where z5 ne . and x ne .;
model d(event='2')=x z5 z5*x;
run;
Model -2 log L
Model 1: X only 2212.7
Model 2: X and G5 (multiplicative ORs) 2203.5
Model 3: X, G5 and X*G5 2202.6
Test for SNP5 (adjusted for X): LRT=9.2 on 1 d.f. p=.002(model 2 vs. modle 1)
Test for "statistical interaction" LRT=0.9 on 1 d.f. p=.34(model 3 vs. model 2)
Joint test for G and G-E effects LRT=10.1 on 2 d.f p=.006(model 3 vs. model 1)
/* g-g "interaction" test assuming linear trend in log OR by SNP5 and SNP10 */
proc logistic data=yahoo;
where z5 ne . and z10 ne .;
model d(event='2')=z5 z10 z5*z10;
run;
/* g-g "interaction" test not assuming linear trend in OR by SNP5 and SNP10 */
proc logistic data=yahoo;
where z5 ne . and z10 ne .;
class z5 z10 (ref='0' param=reference);
model d(event='2')=z5 z10 z5*z10;
run;
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-0.8
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0
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0 1 2
SNP5
log
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Z10=2
Z10=1
Z10=0
/* g-g "interaction" test not assuming linear trend in OR by SNP5 and SNP10 */
data yahoo;
set yahoo;
Z5_Z10=(put(z5, 1.))||(put(z10, 1.));
if z5=. or z10=. then Z5_Z10=' ';
run;
proc freq data=yahoo;
tables z5_z10*z5*z10 / list;
run;
proc logistic data=yahoo;
where z5 ne . and z10 ne .;
class z5_z10 (ref='00' param=reference);
model d(event='2')=z5_z10;
run;
/* fit (constrained) additive interaction between dichotomous g and x */data yahoo; set yahoo; if z5 eq 0 then gcat=0; if z5 gt 0 then gcat=1; if x le .5 and x ne . then xcat=0; if x gt .5 then xcat=1;proc freq data=yahoo; tables gcat*xcat / list;run;proc nlmixed data=yahoo; where gcat ne . and xcat ne .; if (gcat eq 0) and (xcat eq 0) then eta=a; if (gcat eq 0) and (xcat eq 1) then eta=a+b2; if (gcat eq 1) and (xcat eq 0) then eta=a+b1; if (gcat eq 1) and (xcat eq 1) then eta=a+log(exp(b1)+exp(b2)-1); ll = (d=2)*eta - log(1+exp(eta)); model d ~ general(ll); parms a b1 b2=0;run;
Beta_2 is log OR (exposed non carriers)Beta_1 is log OR (carrier unexposed)OR (exposed carrier) is exp(beta_1)+exp(beta_2)-1
/* unconstrained model (to test for departure from additive--risk scale--interaction */proc logistic data=yahoo; model d(event='2')=gcat xcat gcat*xcat; run;proc logistic data=yahoo; class G_X (ref='00' param=reference); model d(event='2')=G_X; run;proc nlmixed data=yahoo; where gcat ne . and xcat ne .; if (gcat eq 0) and (xcat eq 0) then eta=a; if (gcat eq 0) and (xcat eq 1) then eta=a+b2; if (gcat eq 1) and (xcat eq 0) then eta=a+b1; if (gcat eq 1) and (xcat eq 1) then eta=a+b3; ll = (d=2)*eta - log(1+exp(eta)); model d ~ general(ll); parms a b1 b2 b3=0;run;
Constrained -2 log L = 2211.7 Unconstrained -2 log L = 2210.8
LRT is 0.9 on 1 d.f. p=0.34
Beta_2 is log OR (exposed non carriers)Beta_1 is log OR (carrier unexposed)Beta_3 is log OR (exposed carrier)
Power calculations: Quantohttp://hydra.usc.edu/gxe/
G, G-E, G-G, joint G G-E
Set MAF
Set Prev(E)
Set Penetrance Model
Set alpha, target power (N)