Mega2R (version 1.0.2)

DOSKAT: SKAT call back function

Description

Convert the genotypesraw() allele patterns of 0x10001, 0x10002 (or 0x20001), 0x20002, 0 to the numbers 0, 1, 2, 9 for each marker. (Reverse, the order iff allele "1" has the minor allele frequency.) Ignore markers that have no variants (unless allMarkers is TRUE). Finally, invoke SKAT with the converted genotype matrix, Null model saved in envir$obj, and any additionally supplied arguments. Save information about the range and the p.value calculated by SKAT in envir$SKAT_results.

Usage

DOSKAT(markers_arg, range_arg, envir, ...)

Arguments

markers_arg

a data.frame with the following 5 observations:

locus_link

is the ordinal ranking of this marker among all loci

locus_link_fill

is the position of corresponding genotype data in the unified_genotype_table

MarkerName

is the text name of the marker

chromosome

is the integer chromosome number

position

is the integer base pair position of marker

range_arg

one row of a ranges_arg. The latter is a data frame of at least three integer columns. The columns indicate a range: a chromosome number, a start base pair value, and an end base pair value.

envir

'environment' containing SQLite database and other globals

...

extra arguments for SKAT

Value

None

See Also

init_SKAT, Mega2SKAT

Examples

# NOT RUN {
db = system.file("exdata", "seqsimm.db", package="Mega2R")
ENV = init_SKAT(db, verbose = TRUE, allMarkers = FALSE)
Mega2SKAT(ENV$phe[, 3] - 1 ~ 1, "D", gs=1:1)

# }
# NOT RUN {
# donttestcheck: try this below instead if there is time
Mega2SKAT(ENV$phe[, 3] - 1 ~ 1, "D", kernel = "linear.weighted", 
          weights.beta = c(0.5, 0.5), genes=c("CEP104") )
# }
# NOT RUN {
# DOSKAT is called internally to Mega2SKAT. init_SKAT and Mega2SKAT need to be
# called to set up the environment for DOSKAT to run.  You should ignore DOSKAT
# and use Mega2SKAT instead
#
applyFnToRanges(DOSKAT, ENV$refRanges[50:60, ], ENV$refIndices)

# }