Post by fpan on May 8, 2015 3:13:42 GMT
Hi Zhihong
I want to use the GCTA to calculate H2 for some traits, but the dataset I have is exome chip data which includes about 260,000 SNPs, but only 43,000 SNPs have frequency above 0.01, so if I conduct quality control for this dataset, only few SNPs are left for analysis.
Can I still use this data? Are there any methods to solve this problem? Is it possible to impute this data and then perform this analysis?
Or can I analyse it without quality control? can I split the data into two groups as MAF<0.01 and MAF>0.01, and then look at the H2 seperately with these two groups?
Look forward to hearing from you!
Many thanks,
Best wishes,
Feng
I want to use the GCTA to calculate H2 for some traits, but the dataset I have is exome chip data which includes about 260,000 SNPs, but only 43,000 SNPs have frequency above 0.01, so if I conduct quality control for this dataset, only few SNPs are left for analysis.
Can I still use this data? Are there any methods to solve this problem? Is it possible to impute this data and then perform this analysis?
Or can I analyse it without quality control? can I split the data into two groups as MAF<0.01 and MAF>0.01, and then look at the H2 seperately with these two groups?
Look forward to hearing from you!
Many thanks,
Best wishes,
Feng