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I am currently using GAPIT for a Genome-Wide Association Study (GWAS) and have a question regarding the incorporation of covariates in my analysis. I am working with two populations of calves. The populations are divided based on the semen selection of their sires, with one group having positive breeding values for meat tenderness and the other group having negative breeding values. My objective is to associate metabolic levels with the genotypes of the animals.
Given that, my study population consists of only 250 animals, running separate GWAS analyses for each group might be impractical due to the reduced sample size in each subgroup. I am therefore interested in exploring whether it is possible to include this population effect as a covariate in the GWAS analysis within GAPIT.
Specifically, I would like to know if GAPIT can accommodate such covariates, allowing the GWAS to account for these effects and identify significant SNPs for each trait while considering the population differences. For example generating two Manhattan plots per trait (one for each population). Thus, I can compare the results between my groups.
Could you advise on whether this is feasible with GAPIT and, if so, how to implement it?
Thank you!!
The text was updated successfully, but these errors were encountered:
I am currently using GAPIT for a Genome-Wide Association Study (GWAS) and have a question regarding the incorporation of covariates in my analysis. I am working with two populations of calves. The populations are divided based on the semen selection of their sires, with one group having positive breeding values for meat tenderness and the other group having negative breeding values. My objective is to associate metabolic levels with the genotypes of the animals.
Given that, my study population consists of only 250 animals, running separate GWAS analyses for each group might be impractical due to the reduced sample size in each subgroup. I am therefore interested in exploring whether it is possible to include this population effect as a covariate in the GWAS analysis within GAPIT.
Specifically, I would like to know if GAPIT can accommodate such covariates, allowing the GWAS to account for these effects and identify significant SNPs for each trait while considering the population differences. For example generating two Manhattan plots per trait (one for each population). Thus, I can compare the results between my groups.
Could you advise on whether this is feasible with GAPIT and, if so, how to implement it?
Thank you!!
The text was updated successfully, but these errors were encountered: