Post by owen qin on May 15, 2018 0:44:44 GMT
Dear developers,
I am trying to use the GCTA-COJO to pick up independent associated SNPs from single cohort based GWAS (individual-level genotype data are available). There are two different modes available for this task:
(1) gcta64 --bfile individual_level_genotype --cojo-actual-geno
(2) gcta64 --bfile individual_level_genotype --cojo-wind 10000
According to the manual, the "--cojo-actual-geno" will overwrite the "--cojo-wind" and scan all the genome-wide SNPs. The problem is that, in some cases, it is possible to include a huge amount of the genome-wide in the joint model. I can get the significant SNPs after the multiple (joint) regression but there is no information about other non-significant SNPs. Can I know what other SNPs are included in the joint model?
Sometimes there are no overlap SNPs between the results of two modes with the same input. This may raise the question of which mode to be used in the analysis. Knowing what SNPs are included in the joint model would be helpful to make choice.
Thanks,
Owen
I am trying to use the GCTA-COJO to pick up independent associated SNPs from single cohort based GWAS (individual-level genotype data are available). There are two different modes available for this task:
(1) gcta64 --bfile individual_level_genotype --cojo-actual-geno
(2) gcta64 --bfile individual_level_genotype --cojo-wind 10000
According to the manual, the "--cojo-actual-geno" will overwrite the "--cojo-wind" and scan all the genome-wide SNPs. The problem is that, in some cases, it is possible to include a huge amount of the genome-wide in the joint model. I can get the significant SNPs after the multiple (joint) regression but there is no information about other non-significant SNPs. Can I know what other SNPs are included in the joint model?
Sometimes there are no overlap SNPs between the results of two modes with the same input. This may raise the question of which mode to be used in the analysis. Knowing what SNPs are included in the joint model would be helpful to make choice.
Thanks,
Owen