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"))
)
# Subsetting
test_NanoStringRccSet_subset <- function() {
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Endogenous", ],
subset(rcc, CodeClass == "Endogenous"))
#checkEquals(IRanges::NumericList(x = c(a = 1), compress = FALSE),
# weights(signatures(subset(rcc, CodeClass == "Endogenous"))))
checkEquals(rcc[, phenoData(rcc)[["Treatment"]] == "A"],
subset(rcc, select = Treatment == "A"))
checkEquals(weights(signatures(rcc)),
weights(signatures(subset(rcc, select = Treatment == "A"))))
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Endogenous",
phenoData(rcc)[["Treatment"]] == "A"],
subset(rcc, CodeClass == "Endogenous", Treatment == "A"))
#checkEquals(IRanges::NumericList(x = c(a = 1), compress = FALSE),
# weights(signatures(subset(rcc, CodeClass == "Endogenous",
# Treatment == "A"))))
}
test_NanoStringRccSet_subset_in_function <- function() {
subsetFUN1 <- function(object, x) subset(object, CodeClass == x)
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Endogenous", ],
subsetFUN1(rcc, "Endogenous"))
subsetFUN2 <- function(object, x) subset(object, select = Treatment == x)
checkEquals(rcc[, phenoData(rcc)[["Treatment"]] == "A"],
subsetFUN2(rcc, "A"))
subsetFUN3 <-
function(object, x, y) subset(object, CodeClass == x, Treatment == y)
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Endogenous",
phenoData(rcc)[["Treatment"]] == "A"],
subsetFUN3(rcc, "Endogenous", "A"))
}
test_NanoStringRccSet_endogenousSubset <- function() {
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Endogenous", ],
endogenousSubset(rcc))
}
test_NanoStringRccSet_housekeepingSubset <- function() {
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Housekeeping", ],
housekeepingSubset(rcc))
}
test_NanoStringRccSet_negativeControlSubset <- function() {
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Negative", ],
negativeControlSubset(rcc))
}
test_NanoStringRccSet_positiveControlSubset <- function() {
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Positive", ],
positiveControlSubset(rcc))
checkEquals(rcc[featureData(rcc)[["CodeClass"]] == "Positive" &
featureData(rcc)[["ControlConc"]] >= 0.5, ],
positiveControlSubset(rcc, subset = ControlConc >= 0.5))
}
test_NanoStringRccSet_controlSubset <- function() {
checkEquals(rcc[featureData(rcc)[["IsControl"]], ], controlSubset(rcc))
}
test_NanoStringRccSet_nonControlSubset <- function() {
checkEquals(rcc[!featureData(rcc)[["IsControl"]], ], nonControlSubset(rcc))
}
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