For large datasets, for the better performance, we suggest to seperate the SNP files and use clusters for parallel submission.

Download (GAMMA.tar.gz) contains the followings,

  • Pylmm_GAMMA : modified Pylmm for GAMMA : esitmate a kinship matrix : estimate variance components of the data

  • Run GAMMA


  • Test data: see HowToRun.txt

  • License

System requirements

R librarires (gtools, mvtnorm, vegan)

User's guide

  1. Prerequistic

    Estimate a kinship matrix, K. You can esimtate a kinship matrix from genoytpes whatever software you want to use. You can use Pylmm ( 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 ( to estimate the variance components.

  2. 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