solarPolygenic(formula, data, dir, kinship, traits, covlist = "1", covtest = FALSE, screen = FALSE, household = as.logical(NA), transforms = character(0), alpha = 0.05, polygenic.settings = "", polygenic.options = "", verbose = 0, ...)
formula or one that can be coerced to that class.
It is a symbolic description of fixed effects (covariates) to be fitted.
If the model does not have any covariates, then the formula looks like
trait ~ 1, where 1 means the trait mean parameter.as.data.frame to a data frame
are not supported."age^1,2,3#sex" that means sex age agesex age^2 age^2sex age^3 age^3*sex.
The default value is "1".polygenic SOLAR command is called with a combination of -screen -all options.
As a result, cf slot will have p-values in pval column.
The default value is FALSE.polygenic SOLAR command is called with -screen option.
As a result, only significant covariates will be maintained in the model.
The default value is FALSE.as.logical(NA), that means the following behavior in SOLAR.
If data has hhid or similar column,
then the house-hold effect is added to the model and tested by SOLAR.
Otherwise, there is no any variable indicating the house-hold effect
neither in data nor in the model.
If household is TRUE, then polygenic SOLAR command is called
with -keephouse option.
If household is FALSE, then house SOLAR command
is not called previously to calling polygenic SOLAR command
(modeling of the house-hold effect is omitted).availableTransforms.
If the model is univariate, the name of transformation is not necessary and can be omitted.
The default value is character(0).-prob option of polygenic SOLAR command.
That is the probability level for keeping covariates as significant.
The default value in SOLAR is 0.1,
but the default value here is 0.05.
This parameter makes the polygenic SOLAR call to be like polygenic -prob 0.05.polygenic.
For example, the liability threshold model applied to a binary trait (the default behavior in SOLAR).
This behavior is disabled by setting the given argument to "option EnableDiscrete 0".
The default value is "".polygenic SOLAR command.
For example, the comprehensive analysis of a bivariate model might be parametrized
by setting this parameter to "-testrhoe -testrhog -testrhoc -testrhop -rhopse".
See SOLAR help page for polygenic command for more details
(http://solar.txbiomedgenetics.org/doc/91.appendix_1_text.html#polygenic).
The default value is "".0.solarPolygenic.
For example, it might be a parameter log.base for transformTrait function
in the case transform is equal to "log".solarPolygenic class. See solarPolygenicClass.
The polygenic analysis is conducted in the following sequence:
export data to a directory by df2solar function,
form a SOLAR call with a list of settings and options,
execute SOLAR by solar function,
parse output files and
store results in an object of solarPolygenic class (see solarPolygenicClass).
### load data and check out ID names data(dat30) matchIdNames(names(dat30))id famid mo fa sex "ID" "FAMID" "MO" "FA" "SEX"## Not run: # ### basic (univariate) polygenic model # mod <- solarPolygenic(trait1 ~ age + sex, dat30) # # ### (univariate) polygenic model with parameters # mod <- solarPolygenic(trait1 ~ age + sex, dat30, covtest = TRUE) # mod$cf # look at test statistics for covariates # # ### basic (bivariate) polygenic model # mod <- solarPolygenic(trait1 + trait2 ~ 1, dat30) # mod$vcf # look at variance components # # ### (bivariate) polygenic model with trait specific covariates # mod <- solarPolygenic(trait1 + trait2 ~ age + sex(trait1), dat30) # # ### (bivariate) polygenic model with a test of the genetic correlation # mod <- solarPolygenic(trait1 + trait2 ~ 1, dat30, polygenic.options = "-testrhog") # mod$lf # look at a p-value of the test # # ### transforms for (univariate) polygenic model # mod <- mod <- solarPolygenic(trait1 ~ 1, dat30, transforms = "log") # # ### transforms for (bivariate) polygenic model # mod <- solarPolygenic(trait1 + trait2 ~ 1, dat30, # transforms = c(trait1 = "log", trait2 = "inormal")) # # ### SOLAR format of introducing covariates # mod <- solarPolygenic(traits = "trait1", covlist = "age^1,2,3#sex", data = dat30) # mod$cf # 8 covariate terms will be printed # # ## End(Not run)