analysis using MMSCORE
ProbABEL v. 0.2.0-beta (C) Yurii Aulchenko, Lennart C. Karssen, Maksim Struchalin, EMCR

Options in effect:
	 --pheno   = ./mmscore_pheno.PHE
	 --info    = ./mmscore_gen.mlinfo
	 --dose    = ./mmscore_gen.mldose
	 --ntraits = 1
	 --ngpreds = 1
	 --interaction = 0
	 --interaction_only = 0
	 --mmscore = ./mmscore_InvSigma_aj.sex.age.dat
	 --map     = not in output
	 --nids    = estimated from data
	 --chrom   = not in output
	 --out     = mmscore
	 --skipd   = 2
	 --separat = ","
	 --score   = OFF
	 --nohead  = OFF
	 --allcov  = OFF
	 --robust  = OFF
Number of SNPs = 5
Actual number of people in phenofile = 500; using all of these
Linear model: ( height_residuals ) ~ mu +  + SNP_A1
you are runing mmscore...
Reading data ... loaded InvSigma ... loaded genotypic data ... loaded null data ... estimated null model ... formed regression object ... done
Analysis:   0.00 ...100.00 ... done
ProbABEL v. 0.2.0-beta (C) Yurii Aulchenko, Lennart C. Karssen, Maksim Struchalin, EMCR

Options in effect:
	 --pheno   = ./mmscore_pheno.PHE
	 --info    = ./mmscore_gen.mlinfo
	 --dose    = ./mmscore_gen.dose.fvi
	             (using FVF data)
	 --ntraits = 1
	 --ngpreds = 1
	 --interaction = 0
	 --interaction_only = 0
	 --mmscore = ./mmscore_InvSigma_aj.sex.age.dat
	 --map     = not in output
	 --nids    = estimated from data
	 --chrom   = not in output
	 --out     = mmscore_fv
	 --skipd   = 2
	 --separat = ","
	 --score   = OFF
	 --nohead  = OFF
	 --allcov  = OFF
	 --robust  = OFF
Number of SNPs = 5
Actual number of people in phenofile = 500; using all of these
Linear model: ( height_residuals ) ~ mu +  + SNP_A1
you are runing mmscore...
Reading data ... loaded InvSigma ... loaded genotypic data ... loaded null data ... estimated null model ... formed regression object ... done
Analysis:   0.00 ...100.00 ... done
2,5c2,5
< rs735579,A,B,0.5847,0.5847,0.5847,0.5847,491,0.534623,1.63067,0.488552
< rs9088604,A,B,0.5847,0.5847,0.5847,0.5847,497,0.435614,-553.621,1.12808
< rs1413801,A,B,0.5847,0.5847,0.5847,0.5847,492,0.311992,-6.1979,0.576774
< rs4911638,A,B,0.5847,0.5847,0.5847,0.5847,496,0.150202,75.6816,0.592895
---
> rs735579,A,B,0.5847,0.5847,0.5847,0.5847,491,0.534623,1.66126,0.495227
> rs9088604,A,B,0.5847,0.5847,0.5847,0.5847,497,0.435614,0,0
> rs1413801,A,B,0.5847,0.5847,0.5847,0.5847,492,0.311992,-6.19776,0.576737
> rs4911638,A,B,0.5847,0.5847,0.5847,0.5847,496,0.150202,75.8228,0.59293
ProbABEL v. 0.2.0-beta (C) Yurii Aulchenko, Lennart C. Karssen, Maksim Struchalin, EMCR

Options in effect:
	 --pheno   = ./mmscore_pheno.PHE
	 --info    = ./mmscore_gen.mlinfo
	 --dose    = ./mmscore_gen.mlprob
	 --ntraits = 1
	 --ngpreds = 2
	 --interaction = 0
	 --interaction_only = 0
	 --mmscore = ./mmscore_InvSigma_aj.sex.age.dat
	 --map     = not in output
	 --nids    = estimated from data
	 --chrom   = not in output
	 --out     = mmscore_prob
	 --skipd   = 2
	 --separat = ","
	 --score   = OFF
	 --nohead  = OFF
	 --allcov  = OFF
	 --robust  = OFF
Number of SNPs = 5
Actual number of people in phenofile = 500; using all of these
Linear model: ( height_residuals ) ~ mu +  + SNP_A1
you are runing mmscore...
Reading data ... loaded InvSigma ... loaded genotypic data ... loaded null data ... estimated null model ... formed regression object ... done
Analysis:   0.00 ...100.00 ... done
ProbABEL v. 0.2.0-beta (C) Yurii Aulchenko, Lennart C. Karssen, Maksim Struchalin, EMCR

Options in effect:
	 --pheno   = ./mmscore_pheno.PHE
	 --info    = ./mmscore_gen.mlinfo
	 --dose    = ./mmscore_gen.prob.fvi
	             (using FVF data)
	 --ntraits = 1
	 --ngpreds = 2
	 --interaction = 0
	 --interaction_only = 0
	 --mmscore = ./mmscore_InvSigma_aj.sex.age.dat
	 --map     = not in output
	 --nids    = estimated from data
	 --chrom   = not in output
	 --out     = mmscore_prob_fv
	 --skipd   = 2
	 --separat = ","
	 --score   = OFF
	 --nohead  = OFF
	 --allcov  = OFF
	 --robust  = OFF
Number of SNPs = 5
Actual number of people in phenofile = 500; using all of these
Linear model: ( height_residuals ) ~ mu +  + SNP_A1
you are runing mmscore...
Reading data ... loaded InvSigma ... loaded genotypic data ... loaded null data ... estimated null model ... formed regression object ... done
Analysis:   0.00 ...100.00 ... done
2,4c2,4
< rs735579,A,B,0.5847,0.5847,0.5847,0.5847,491,0.534623,0,0,-1232.55
< rs9088604,A,B,0.5847,0.5847,0.5847,0.5847,497,0.435614,0,0,-2135.06
< rs1413801,A,B,0.5847,0.5847,0.5847,0.5847,492,0.311992,0.885537,0.569736,-1249.34
---
> rs735579,A,B,0.5847,0.5847,0.5847,0.5847,491,0.534623,0,0,-1232.46
> rs9088604,A,B,0.5847,0.5847,0.5847,0.5847,497,0.435614,-17.636,0.216121,-2433.23
> rs1413801,A,B,0.5847,0.5847,0.5847,0.5847,492,0.311992,0.846902,0.569387,-1249.14