GENERAL INPUT FILES

The input files include at least a data file and a pedigree file. They can be specified with the -d and -p parameters respectively. Using both these options, the command line will look like this:

   prompt> poly -d ex.dat -p ex.ped

Simple models can be specified on the command line without requiring a model input file:
--trait trait_names specifies one or more traits to be analyzed. All traits will be analyzed if not specified.
--covariate covariate_names specifies covariates to be included in the model. No covariates will be adjusted if not specified.
--normalize normalizes trait(s) through inverse normal transformation prior to analysis.

For example, the following command applies inverse normal transformation to traits HEIGHT and WEIGHT, and carries out polygenic analyses adjusting for sex and age:

   prompt> poly -d ex.dat -p ex.ped --trait HEIGHT,WEIGHT --cov sex,age --norm 

When the model you would like to specify is getting more complicated, a model input file can be quite helpful for your analysis. A model input file looks like this:

   covdef age2 cage 2 ^
   covariate sex age cage2
   variance pa pe pd

   model d
   norm on
   traitall
   

   prompt> poly -d ex.dat -p ex.ped -t ex.mod 
   

Elements of a model input file include:

• covdef new_covariate_name postorder_expression defines a new covariate new_covariate_name, interpreting "postorder_expression" as a postfix (Reverse Polish Notation) expression
• traitcopy trait_name covariate_name creats a new trait by copying an existing covariate
• model model_name starts a model definition and performs a polygenic analysis
• covariate covaraite_list specifies all covariates in the model
• variance variance_list specifies all variance components in the model
  • pa: polygenic additive variance
  • pe: polygenic random environmental variance
  • pd: polygenic dominant variance
  • ph: polygenic sibling-shared variance
  • px: polygenic X-link variance
  • pm: mitochondria variance
  • ha: scaled polygenic additive variance
  • he: scaled polygenic random environmental variance
  • hd: scaled polygenic dominant variance
  • hh: scaled polygenic sibling-shared variance
• heterogeneity covarariate_name variance_list heterogeneity in covarariate_name
  • a2: heterogeneity of genetic variance component
  • e2: heterogeneity of environmental variance component
  • h2: heterogeneity of total variance component (with the same heritability)
  • a3: heterogeneity of genetic variance component as well as underlying QTLs (thus 3 parameters for genetic variance component)
  • off: no heterogeneity
• norm on specifies an inverse normal transformation
• trait trait_name specifies the trait of interest
• traitall indicates the analysis is applied to all traits
• bivar model_1 model_2 performs bivariate trait analysis for two traits in model_1 and model_2
• biall indicates the bivariate trait analysis is applied to all trait pairs
• multivar model_list performs multivariate trait analysis for multiple traits in model_list

REFERENCE