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best.trans.eQTLs(smpack, rhs, genechrnum, snpchrnum, K = 20, targdirpref = "tsco", batchsize = 200, radius = 2e+06, genequeryprefix = "", snploadprefix = "chr", snplocprefix = "chr", geneannopk, snpannopk, exFilter = function(x) x, smFilter = function(x) x, geneApply = lapply, SSgen = GGBase::getSS)
smlSet-class
instances
can be generated using getSS
snp.rhs.tests
for covariate or stratification adjustments;
for permutation analysis, covariates should be handled via regressOut
as.character(1:22)
for
somatic genes in human studies
ffrowapply
as scores are filtered from comprehensive testing to fill
the buffer
smpack
requires a prefix to the snpchrnum
token for getSS
retrieval of smlSet
instance
snplocs
calls
transManager-class
## Not run:
# if (.Platform$OS.type != "windows") { # ff overwrites failing 5.IX.12
# nsFilter2 = function(sms, var.cutoff=.5) {
# alliq = apply(exprs(sms),1,IQR)
# qs = quantile(alliq,var.cutoff, na.rm=TRUE)
# sms[ which(alliq > qs), ]
# }
# thefilt = function(x) GTFfilter( nsFilter2 (clipPCs(x, 1:10), var.cutoff=.95 ), lower=.05 )
# tfile = tempfile()
# tfold = dir.create(tfile)
# t1 = best.trans.eQTLs( "GGdata", ~1, as.character(20:22), "22",
# geneannopk="illuminaHumanv1.db", snpannopk= snplocsDefault(),
# smFilter=thefilt, snploadprefix="", snplocprefix="ch", targdirpref=tfile)
# tt1 = transTab(t1)
# tt1o = tt1[ order(tt1[,"sumchisq"], decreasing=TRUE), ][1:10,]
# tt1o
# }
# ## End(Not run)
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