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Options

Options Attribute Default Detail
–single-trait flag – to implement single trait model.
–multi-trait flag – to implement multiple traits model.
–make-xrm flag – to construct and output relationship matrix.
–trans-xrm flag – to transform file format of relationship matrix.
–mme flag – to solve the mixed model equation with provided (co)variance components.
–snp-effect flag – to compute and output snp effect.
–maf flag – to compute the minor allele frequency.
–mating flag – to implement genomic mating.
–inbreeding flag – to calculate the inbreeding coefficient.
–pheno file – the path and name of phenotype file, header should be included, missing value should be represented by “NA”.
–pheno-pos int 2 the position of the analyzed phenotype in columns of phenotype file. For multiple traits, please use comma as separator.
–pedigree file – the path and name of pedigree file, header should be included, the order of columns should be “id”, “father”, “mother”.
–bfile file – the prefix of genotype files in plink binary format.
–gebv file – the estimated genomic breeding values, the first column should be id, header should be included.
–score file – the estimated SNP effects, the first column should be SNP id, the rest columns are the SNP effects, header should be included.
–xrm file – the prefix of binary relationship matrix (*.bin and *.id). For multiple relationship matrix, please use comma as separator.
–dcovar int – the position of the discrete covariates (fixed effects, e.g. sex, year, …) in columns of phenotype file (e.g. “–dcovar 4,5”). For interaction, please use colon as separator (e.g. “–dcovar 4,5,4:5”).
–qcovar int – the position of the quantitative covariates (e.g. height, weight, …) in columns of phenotype file.
–rand int – the position of the random effects in columns of phenotype file. For interaction, please use colon as separator.
–rand-gxe int:file – a mixture of digital value and prefix of XRM, specify genetic-environment interaction (e.g. “–rand-gxe 2:demo.GA”).
–add flag – additive genetic effect.
–add-inv flag – whether to compute the inverse of additive relationship matrix.
–dom flag – dominant genetic effect.
–dom-inv flag – whether to compute the inverse of dominant relationship matrix.
–vc-priors double – the prior values of variance components for all random effects, please use comma as separator within a trait, and use space as separator among traits.
–covc-priors double – the prior values of co-variance components among traits for all ‘xrm’, please use comma as separator among traits, and use space as separator among ‘xrm’.
–snp-weight file – the path and name of a file containing weights for all SNPs when constructing GRM and calculating SNP effects, the fist column shoud be SNP id.
–vc-method text AI the algorithms (AI, EM, EMAI, HE, HI) for variance components estimation.
–tol double 1.00E-06 the tolerance for convergence of variance components estimation.
–ai-maxit int 20 the maximum number of iteration for AIREML.
–em-maxit int 20 the maximum number of iteration for EMREML.
–alpha double 0.05 weight of pedigree based relationship matrix when constructing H matrix for SSGBLUP model.
–ridge-value double 0 ridge regression value for solving uninvertible square matrix.
–triangle flag – input/output a triangle matrix (in format of ‘i j value’).
–xrm-txt file – the file path and name of relationship matrix in text format.
–xrm-id file – the file path and name of id for all individuals.
–keep file – the path and name of a file listing individuals to be used in analysis.
–remove file – the path and name of a file listing individuals to be removed in analysis.
–extract file – the path and name of a file listing markers to be used in analysis.
–exclude file – the path and name of a file listing markers to be removed in analysis.
–pcg flag – to solve the system of linear equations A*x = b for x using the Preconditioned Conjugate Gradients Method.
–pcg-num int 0 the maximum number of iteration for Preconditioned Conjugate Gradients Method.
–step int 10000 the number of markers that are loaded into RAM at a time when constructing GRM, smaller step helps to reduce the memory cost, but would cause lower computational efficiency.
–float-prec flag – whether to use float precision, it can help to reduce the memory cost in analysis.
–threads int 0 the number of threads used for analysis.
–out text hiblup the prefix of output files.