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Documentation
For large datasets, for the better performance, we suggest to seperate the SNP files and use clusters for parallel submission.
Download
GAMMA.zip (GAMMA.tar.gz) contains the followings,
System requirements
R librarires (gtools, mvtnorm, vegan)
User's guide
Prerequistic
Estimate a kinship matrix, K. You can esimtate a kinship matrix from genoytpes whatever software you want to use. You can use Pylmm (pylmmKinship.py) to esimtates a kinship matrix.
Estimate variance components sigma_g^2 and sigma_e^2 of the data. You can estimate the compoenents whatever software you want to use. You can use Pylmm (pylmmGWAS_multiPhHeri.py) to estimate the variance components.
Run GAMMA
Rotate the genotypes and phenotypes space utiling the heritability estimates (median of all the phenotypes).
Usage: R CMD BATCH --args -Xpath=[sample x snp file] -Kpath=[sample x sample kinship file] -Ypath=[sample x phenotype file] -VCpath=[heritability estimates, 1st column is Vg estimates and 2nd column is Ve estimates] -outputPath=[pvalues] GAMMA.R GAMMA.log
♦ Pylmm is a linear mixed model solver developed in our group (for the details see Pylmm). We have modified Pylmm for GAMMA which is included in Pylmm_GAMMA.
For the details or any other questions, please contact Jong Wha J Joo
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