Nothing
#context("detect AI from ASEset")
#
#test_that(paste("detectAI from ASEset results and accessors, return.class='DetectedAI',",
# "multiple samples, multipliple SNPs"), {
#
# #prepare testdata
# data(ASEset)
# x <- ASEset
#
# #make this when the new reference fasta file is in place
# res <- detectAI(x,strand="*", threshold.count.sample=1)
#
# #check row and colnames
# expect_that(rownames(res), equals(rownames(x)))
# expect_that(colnames(res), equals(colnames(x)))
#
# #check strand
# expect_that(rownames(res), equals(rownames(x)))
#
# #check reference.frequency
# expect_that(as.vector(referenceFrequency(res))[1:3], equals(c(0.8000000, 0.8076923, NaN)))
# expect_that(round(referenceFrequency(res)[57:60],7), equals(c(NaN, 0.7656250, 0.8163265, NaN)))
#
# #check threshold.frequency
# expect_that(thresholdFrequency(res)[1:3], equals(c(TRUE,TRUE,NA)))
# expect_that(thresholdFrequency(res)[57:60], equals(c(NA, TRUE, TRUE, NA)))
#
# #check threshold.count.sample
# expect_that(thresholdCountSample(res)[1:3], equals(c(TRUE,TRUE,FALSE)))
# expect_that(thresholdCountSample(res)[57:60], equals(c(FALSE, TRUE, TRUE, FALSE)))
#
# #check threshold.delta.frequency
# expect_that(thresholdDeltaFrequency(res)[1:3], equals(c(TRUE,TRUE,NA)))
# expect_that(thresholdDeltaFrequency(res)[57:60], equals(c(NA, TRUE, TRUE, NA)))
#
# #check threshold.pvalue
# expect_that(thresholdPvalue(res)[1:3], equals(c(TRUE,TRUE,NA)))
# expect_that(thresholdPvalue(res)[57:60], equals(c(NA, TRUE, TRUE, NA)))
#
#})
#
#
#
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