Post date: May 29, 2014 5:18:54 PM
I ran single SNP linear mixed models in gemma to test for individual SNP effects and get MLE of the null (polygenic) PVE. The commands are below. I did this for all treatments and treatment combinations. Note that in this case you can include covariates, so I did not work with residuals for survival, but instead included plant and population as covariates. I used the normal quantile transformed weights, so covariates were not needed. The results are in projects/lycaeides_hostplant/melGemma/lmm_out/. Note that the '2' files are survival whereas the others are for weight. There are a few significant hits at genome-wide significance (p < alpha = 0.05 / no. loci), but more for 'all' and SLA on Ac (survival, but this is likely because of the imbalance in number of survivors, and not interesting). I have an perl script (plotManhat.pl) that makes a bunch of individual Manhattan plots, but I need to edit this to make nicer figures. Also, I might use the LRT p-value rather than the Wald (though they are almost equivalent).
gemma -g ../geno_glaTrtMs.txt -p ../pheno_glaTrtMs.txt -gk 1 -o k_glaMs
gemma -g ../geno_glaTrtMs.txt -p ../pheno_glaTrtMs.txt -k output/k_glaMs.cXX.txt -a ../annotation.txt -lmm 4 -o lm_glaMs
gemma -g ../geno_glaTrtAc.txt -p ../pheno_glaTrtAc.txt -gk 1 -o k_glaAc
gemma -g ../geno_glaTrtAc.txt -p ../pheno_glaTrtAc.txt -k output/k_glaAc.cXX.txt -a ../annotation.txt -lmm 4 -o lm_glaAc
gemma -g ../geno_slaTrtMs.txt -p ../pheno_slaTrtMs.txt -gk 1 -o k_slaMs
gemma -g ../geno_slaTrtMs.txt -p ../pheno_slaTrtMs.txt -k output/k_slaMs.cXX.txt -a ../annotation.txt -lmm 4 -o lm_slaMs
gemma -g ../geno_slaTrtAc.txt -p ../pheno_slaTrtAc.txt -gk 1 -o k_slaAc
gemma -g ../geno_slaTrtAc.txt -p ../pheno_slaTrtAc.txt -k output/k_slaAc.cXX.txt -a ../annotation.txt -lmm 4 -o lm_slaAc
gemma -g ../geno_glaTrtMs.txt -p ../pheno_glaTrtMs.txt -k k_glaMs.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -o lm_glaMs2
gemma -g ../geno_glaTrtAc.txt -p ../pheno_glaTrtAc.txt -k output/k_glaAc.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -o lm_glaAc2
gemma -g ../geno_slaTrtMs.txt -p ../pheno_slaTrtMs.txt -k output/k_slaMs.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -o lm_slaMs2
gemma -g ../geno_slaTrtAc.txt -p ../pheno_slaTrtAc.txt -k output/k_slaAc.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -o lm_slaAc2
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gemma -g ../geno_combGla.txt -p ../pheno_gla.txt -gk 1 -o k_gla
gemma -g ../geno_combGla.txt -p ../pheno_gla.txt -k output/k_gla.cXX.txt -a ../annotation.txt -lmm 4 -o lm_gla
gemma -g ../geno_combSla.txt -p ../pheno_sla.txt -gk 1 -o k_sla
gemma -g ../geno_combSla.txt -p ../pheno_sla.txt -k output/k_sla.cXX.txt -a ../annotation.txt -lmm 4 -o lm_sla
gemma -g ../geno_combAc.txt -p ../pheno_ac.txt -gk 1 -o k_ac
gemma -g ../geno_combAc.txt -p ../pheno_ac.txt -k output/k_ac.cXX.txt -a ../annotation.txt -lmm 4 -o lm_ac
gemma -g ../geno_combMs.txt -p ../pheno_ms.txt -gk 1 -o k_ms
gemma -g ../geno_combMs.txt -p ../pheno_ms.txt -k output/k_ms.cXX.txt -a ../annotation.txt -lmm 4 -o lm_ms
gemma -g ../geno_combAll.txt -p ../pheno_all.txt -gk 1 -o k_all
gemma -g ../geno_combAll.txt -p ../pheno_all.txt -k output/k_all.cXX.txt -a ../annotation.txt -lmm 4 -o lm_all
gemma -g ../geno_combGla.txt -p ../pheno_gla.txt -k output/k_gla.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -c covar_gla.txt -o lm_gla2
gemma -g ../geno_combSla.txt -p ../pheno_sla.txt -k output/k_sla.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -c covar_sla.txt -o lm_sla2
gemma -g ../geno_combAc.txt -p ../pheno_ac.txt -k output/k_ac.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -c covar_ac.txt -o lm_ac2
gemma -g ../geno_combMs.txt -p ../pheno_ms.txt -k output/k_ms.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -c covar_ms.txt -o lm_ms2
gemma -g ../geno_combAll.txt -p ../pheno_all.txt -k output/k_all.cXX.txt -a ../annotation.txt -lmm 4 -n 2 -c covar_all.txt -o lm_all2