Mega2SKAT | R Documentation |
Execute the SKAT function on the first gs default gene transcripts (gs = 1:100). Update the envir$SKAT_results data frame with the results.
Mega2SKAT(f, ty, gs = 1:100, genes = NULL, skat = SKAT::SKAT, envir = ENV, ...)
f |
SKAT_Null_Model formula. If this is non NULL, envir$obj is initialized by calling
SKAT_Null_Model(f, out_type = ty). If you need to specify additional arguments to the Model
viz. (data, Adjustment, n.Resampling, type.Resampling)
or need to use a different model viz. SKAT_NULL_emmaX, |
ty |
type of phenotype C/D = Continuous/Binary 5 (internal type 1/2) |
gs |
a subrange of the default transcripts (refRanges) over which to calculate the DOSKAT function. |
genes |
a list of genes over which to calculate the DOSKAT function. The value, "*", means use all the transcripts in the selected Bioconductor database. If genes is NULL, the gs range of the internal refRanges will be used. |
skat |
alternate SKAT function, viz. SKATBinary, SKAT_CommonRare. If it is also necessary is to pass additional arguments to the SKAT function, they may be added to the end of the Mega2SKAT function and will be passed. See examples |
envir |
'environment' containing SQLite database and other globals |
... |
extra arguments for SKAT |
None the data frame with the results is stored in the environment and named SKAT_results, viz. envir$SKAT_results
The SKAT_Null_Model
is called if the formula, f, is not NULL. A helper function
SKAT3arg
is defined for the 3 argument callback function which in turn calls
DOSKAT
with the appropriate arguments (including those additional to the
Mega2SKAT
function).
init_SKAT
db = system.file("exdata", "seqsimm.db", package="Mega2R")
ENV = init_SKAT(db, verbose = FALSE, allMarkers = FALSE)
ENV$verbose = FALSE
ENV$SKAT_results = ENV$SKAT_results[0, ]
Mega2SKAT(ENV$phe[, 3] - 1 ~ 1, "D", kernel = "linear.weighted",
weights.beta = c(0.5, 0.5), gs=50:60 )
# donttestcheck: try this below if there is time
Mega2SKAT(ENV$phe[, 3] - 1 ~ 1, "D", kernel = "linear.weighted",
weights.beta = c(0.5, 0.5), genes=c("CEP104") )
ENV$SKAT_results
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