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context("Test plot functions.")
set.seed(42)
mat <- matrix(data=rpois(1000, lambda=10), ncol=10)
rownames(mat) <- paste("gene", 1:nrow(mat), sep="")
colnames(mat) <- paste("sample", 1:ncol(mat), sep="")
es <- newSeqExpressionSet(mat)
test_that("setters and getters works", {
counts(es) <- mat
expect_equal(counts(es), mat)
normCounts(es) <- mat
expect_equal(normCounts(es), mat)
})
test_that("between-lane normalization works", {
es <- newSeqExpressionSet(mat)
es2 <- newSeqExpressionSet(mat)
# full
norm_mat <- betweenLaneNormalization(mat, which="full")
normCounts(es2) <- norm_mat
es3 <- betweenLaneNormalization(es, which="full")
expect_equal(es2, es3)
# median
norm_mat <- betweenLaneNormalization(mat, which="median")
normCounts(es2) <- norm_mat
es3 <- betweenLaneNormalization(es, which="median")
expect_equivalent(es2, es3)
# upper
norm_mat <- betweenLaneNormalization(mat, which="upper")
normCounts(es2) <- norm_mat
es3 <- betweenLaneNormalization(es, which="upper")
expect_equivalent(es2, es3)
})
test_that("within-lane normalization works", {
gc <- rnorm(100)
es <- newSeqExpressionSet(mat, featureData = data.frame(gc=gc, row.names=rownames(mat)))
es2 <- es
# full
norm_mat <- withinLaneNormalization(mat, gc, which="full")
normCounts(es2) <- norm_mat
es3 <- withinLaneNormalization(es, "gc", which="full")
expect_equal(es2, es3)
# median
norm_mat <- withinLaneNormalization(mat, gc, which="median")
normCounts(es2) <- norm_mat
es3 <- withinLaneNormalization(es, "gc", which="median")
expect_equivalent(es2, es3)
# upper
norm_mat <- withinLaneNormalization(mat, gc, which="upper")
normCounts(es2) <- norm_mat
es3 <- withinLaneNormalization(es, "gc", which="upper")
expect_equivalent(es2, es3)
# loess
norm_mat <- withinLaneNormalization(mat, gc, which="loess")
normCounts(es2) <- norm_mat
es3 <- withinLaneNormalization(es, "gc", which="loess")
expect_equivalent(es2, es3)
})
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