rcc <-
NanoStringRccSet(assayData =
matrix(0:11, 4L, 3L,
dimnames = list(letters[1:4], sprintf("%s.RCC", LETTERS[1:3]))),
phenoData =
AnnotatedDataFrame(data.frame(Treatment = c("A", "A", "B"),
Age = c(58L, 42L, 27L),
row.names = sprintf("%s.RCC", LETTERS[1:3]),
stringsAsFactors = FALSE),
dimLabels = c("sampleNames", "sampleColumns")),
featureData =
AnnotatedDataFrame(data.frame(CodeClass = c("Endogenous", "Positive", "Negative", "Housekeeping"),
GeneName = letters[1:4],
Accession = letters[1:4],
IsControl = c(FALSE, TRUE, TRUE, TRUE),
ControlConc = c(NA_real_, 0.125, 0, NA_real_),
row.names = letters[1:4],
stringsAsFactors = FALSE),
dimLabels = c("featureNames", "featureColumns")),
annotation = "rlffile",
protocolData =
AnnotatedDataFrame(data.frame(FileVersion = numeric_version(rep("1.7", 3L)),
SoftwareVersion = numeric_version(rep("4.0.0.3", 3L)),
SystemType = rep("Gen2", 3L),
SampleID = letters[1:3],
SampleOwner = rep("", 3L),
SampleComments = rep("DNA-RNA-Protein", 3L),
SampleDate = as.Date(rep("1999-12-31", 3L)),
SystemAPF = rep("n6_vDV1", 3L),
AssayType = rep(NA_character_, 3L),
LaneID = 1:3,
FovCount = rep(280L, 3L),
FovCounted = 1:3,
ScannerID = rep("a", 3L),
StagePosition = 1:3,
BindingDensity = c(0.75, 1, 1.25),
CartridgeID = letters[1:3],
CartridgeBarcode = rep("", 3L),
row.names = sprintf("%s.RCC", LETTERS[1:3]),
stringsAsFactors = FALSE),
NanoStringNCTools:::.rccMetadata[["protocolData"]],
dimLabels = c("sampleNames", "sampleColumns"))
)
# Looping
test_NanoStringRccSet_utils_assayDataApply <- function() {
rcc2 <- transform(rcc, log1p_exprs = log1p(exprs))
checkIdentical(apply(exprs(rcc2), 1L, mean), assayDataApply(rcc2, 1L, mean))
checkIdentical(apply(exprs(rcc2), 2L, mean), assayDataApply(rcc2, 2L, mean))
checkIdentical(apply(assayDataElement(rcc2, "log1p_exprs"), 1L, mean),
assayDataApply(rcc2, 1L, mean, elt = "log1p_exprs"))
checkIdentical(apply(assayDataElement(rcc2, "log1p_exprs"), 2L, mean),
assayDataApply(rcc2, 2L, mean, elt = "log1p_exprs"))
}
test_NanoStringRccSet_utils_signatureScoresApply <- function() {
rcc2 <- transform(rcc, log1p_exprs = log1p(exprs))
checkIdentical(apply(signatureScores(rcc2), 1L, mean),
signatureScoresApply(rcc2, 1L, mean))
checkIdentical(apply(signatureScores(rcc2), 2L, mean),
signatureScoresApply(rcc2, 2L, mean))
checkIdentical(apply(signatureScores(rcc2, "log1p_exprs"), 1L, mean),
signatureScoresApply(rcc2, 1L, mean, elt = "log1p_exprs"))
checkIdentical(apply(signatureScores(rcc2, "log1p_exprs"), 2L, mean),
signatureScoresApply(rcc2, 2L, mean, elt = "log1p_exprs"))
}
# Transforming
test_NanoStringRccSet_utils_transform <- function() {
rcc2 <- transform(rcc,
exprs_scaled = sweep(exprs, 2L, c(2, 1, 0.5), FUN = "*"),
exprs_thresh = pmax(exprs_scaled - 2L, 0L))
checkTrue(validObject(rcc2))
checkEquals(sweep(exprs(rcc), 2L, c(2, 1, 0.5), FUN = "*"),
assayDataElement(rcc2, "exprs_scaled"))
checkEquals(pmax(sweep(exprs(rcc), 2L, c(2, 1, 0.5), FUN = "*") - 2L, 0L),
assayDataElement(rcc2, "exprs_thresh"))
checkIdentical(list(exprs_scaled = substitute(sweep(exprs, 2L, c(2, 1, 0.5), FUN = "*")),
exprs_thresh = substitute(pmax(exprs_scaled - 2L, 0L))),
preproc(rcc2))
}
# Evaluating
test_NanoStringRccSet_utils_with <- function() {
nms <- sort(c(assayDataElementNames(rcc), fvarLabels(rcc), svarLabels(rcc),
"signatures", "design"))
checkIdentical(nms, with(rcc, ls()))
# calculate means across Features
checkIdentical(assayDataApply(rcc, 1L, mean),
with(rcc, apply(exprs, 1L, mean)))
# calculate means across Samples
checkIdentical(assayDataApply(rcc, 2L, mean),
with(rcc, apply(exprs, 2L, mean)))
}
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