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test_protein.R
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test_protein.R
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library(GeomxTools)
library(testthat)
datadir <- system.file("extdata","DSP_Proteogenomics_Example_Data",
package = "GeomxTools")
DCCFiles <- unzip(zipfile = file.path(datadir, "/DCCs.zip"))
PKCFiles <- unzip(zipfile = file.path(datadir, "/pkcs.zip"))
SampleAnnotationFile <- file.path(datadir, "Annotation.xlsx")
RNAData <- suppressWarnings(readNanoStringGeoMxSet(dccFiles = DCCFiles,
pkcFiles = PKCFiles,
phenoDataFile = SampleAnnotationFile,
phenoDataSheet = "Annotations",
phenoDataDccColName = "Sample_ID",
protocolDataColNames = c("Tissue",
"Segment_Type",
"ROI.Size"),
configFile = NULL,
analyte = "RNA",
phenoDataColPrefix = "",
experimentDataColNames = NULL))
proteinData <- suppressWarnings(readNanoStringGeoMxSet(dccFiles = DCCFiles,
pkcFiles = PKCFiles,
phenoDataFile = SampleAnnotationFile,
phenoDataSheet = "Annotations",
phenoDataDccColName = "Sample_ID",
protocolDataColNames = c("Tissue",
"Segment_Type",
"ROI.Size"),
configFile = NULL,
analyte = "protein",
phenoDataColPrefix = "",
experimentDataColNames = NULL))
# Spec 11: Only a single analyte is read in to a GeomMxSet object.:------
testthat::test_that("Datasets can be subset by given analyte", {
expect_true(analyte(proteinData) == "Protein")
expect_true(analyte(proteinData) != "RNA")
expect_true(analyte(RNAData) == "RNA")
expect_true(analyte(RNAData) != "Protein")
expect_true(featureType(RNAData) == "Probe")
expect_true(featureType(proteinData) == "Target")
expect_error(suppressWarnings(readNanoStringGeoMxSet(dccFiles = DCCFiles,
pkcFiles = PKCFiles,
phenoDataFile = SampleAnnotationFile,
phenoDataSheet = "Annotations",
phenoDataDccColName = "Sample_ID",
protocolDataColNames = c("Tissue",
"Segment_Type",
"ROI.Size"),
configFile = NULL,
analyte = "TEST",
phenoDataColPrefix = "",
experimentDataColNames = NULL)))
expect_true(all(proteinData@annotation %in% paste0(unique(fData(proteinData)$Module), ".pkc")))
expect_true(all(RNAData@annotation %in% paste0(unique(fData(RNAData)$Module), ".pkc")))
})
RNAData <- aggregateCounts(RNAData)
proteinData_seqQC <- setSegmentQCFlags(proteinData,
qcCutoffs=list(minSegmentReads=1000,
percentAligned=80,
percentSaturation=50))
proteinData_background <- setBackgroundQCFlags(proteinData_seqQC,
qcCutoffs=list(minNegativeCount=10,
maxNTCCount=60))
proteinData <- setSegmentQCFlags(proteinData,
qcCutoffs=list(minNuclei=20,
minArea=16000,
minNegativeCount=10,
maxNTCCount=60,
minSegmentReads=1000,
percentAligned=80,
percentSaturation=50))
RNAData_seqQC <- setSeqQCFlags(RNAData,
qcCutoffs=list(minSegmentReads=1000,
percentAligned=80,
percentSaturation=50))
RNAData_background <- setBackgroundQCFlags(RNAData_seqQC,
qcCutoffs=list(minNegativeCount=10,
maxNTCCount=60))
RNAData <- setSegmentQCFlags(RNAData,
qcCutoffs=list(minNuclei=20,
minArea=16000,
minNegativeCount=10,
maxNTCCount=60,
minSegmentReads=1000,
percentAligned=80,
percentSaturation=50))
# Spec 20: The appropriate segment QC flags shall be added to a protein dataset.:------
test_that("Correct segment flags are added to protein data",{
expect_false("LowNegatives" %in% colnames(protocolData(proteinData)$QCFlags))
expect_false("LowNegatives" %in% colnames(protocolData(proteinData_seqQC)$QCFlags))
expect_false("LowNegatives" %in% colnames(protocolData(proteinData_background)$QCFlags))
expect_equal(ncol(protocolData(proteinData_seqQC)$QCFlags), ncol(protocolData(proteinData_background)$QCFlags))
expect_equal(ncol(protocolData(proteinData_seqQC)$QCFlags), ncol(protocolData(proteinData)$QCFlags))
expect_gt(ncol(protocolData(RNAData_background)$QCFlags), ncol(protocolData(RNAData_seqQC)$QCFlags))
expect_equal(ncol(protocolData(RNAData_background)$QCFlags), ncol(protocolData(RNAData)$QCFlags))
})
# Spec 21: A warning is given if protein data is run through setBioProbeQCFlags.:------
test_that("Warnings are given if protein data is run through setBioProbeQCFlags", {
expect_warning(expect_warning(expect_warning(setBioProbeQCFlags(proteinData,
qcCutoffs=list(minProbeRatio=0.1,
percentFailGrubbs=20)))))
})
igg.names <- iggNames(proteinData)
hk.names <- hkNames(proteinData)
HOUSEKEEPERS <- c(
"C1orf43", "GPI", "OAZ1", "POLR2A", "PSMB2", "RAB7A",
"SDHA", "SNRPD3", "TBC1D10B", "TPM4", "TUBB", "UBB"
)
# Spec 1: igg.names shall return the expected target names.:------
test_that("Expected IgGs are returned",{
expect_true(all(grepl(pattern = "IgG", igg.names)))
expect_equal(length(igg.names), length(grep(pattern = "IgG", fData(proteinData)$TargetName)))
expect_true(all(igg.names == fData(proteinData)$TargetName[fData(proteinData)$CodeClass == "Negative"]))
expect_warning(iggNames(RNAData))
})
# Spec 2: hk.names shall return the expected target names.:------
test_that("Expected HK are returned",{
expect_true(all(hk.names == fData(proteinData)$TargetName[fData(proteinData)$CodeClass == "Control"]))
expect_warning(hkNames(RNAData))
})
test_that("Concordance plots are plotted", {
expect_error(plotConcordance(igg.names, proteinData, "Segment_Typ"))
expect_error(fig <- plotConcordance(igg.names, proteinData, "Segment_Type"), NA)
expect_true(class(fig)[1] == "gg")
expect_error(fig, NA)
expect_error(fig <- plotConcordance(igg.names, proteinData, "Tissue"), NA)
expect_true(class(fig)[1] == "gg")
expect_error(fig, NA)
expect_error(fig <- plotConcordance(HOUSEKEEPERS[1:4], RNAData, "Segment_Type"), NA)
expect_true(class(fig)[1] == "gg")
expect_error(fig, NA)
})
proteinData <- normalize(proteinData, norm_method = "hk", toElt="hk_norm")
proteinData <- normalize(proteinData, norm_method = "hk", toElt="hk_norm_givenHK", housekeepers = hk.names)
proteinData <- normalize(proteinData, norm_method = "neg", toElt="neg_norm")
proteinData <- normalize(proteinData, norm_method = "quant", toElt="q3_norm")
proteinData <- normalize(proteinData, norm_method = "subtractBackground", toElt="bgSub_norm")
# Spec 13: All normalization methods work on protein data.:------
test_that("Protein data is normalized",{
expect_true(all(proteinData@assayData$exprs != proteinData@assayData$hk_norm))
expect_true(all(proteinData@assayData$exprs != proteinData@assayData$neg_norm))
expect_true(all(proteinData@assayData$exprs != proteinData@assayData$q3_norm))
expect_true(all(proteinData@assayData$exprs != proteinData@assayData$bgSub_norm))
expect_equal(proteinData@assayData$hk_norm, proteinData@assayData$hk_norm_givenHK)
expect_true(all(c("hk_norm_hkFactors", "neg_norm_negFactors", "q3_norm_qFactors") %in%
colnames(pData(proteinData))))
})
normfactors <- computeNormalizationFactors(object = proteinData)
normfactors_area <- computeNormalizationFactors(object = proteinData,
area = "AOI.Size.um2")
normfactors_area_nuc <- computeNormalizationFactors(object = proteinData,
area = "AOI.Size.um2",
nuclei = "Nuclei.Counts")
# Spec 3: computeNormalizationFactors and normalize calculations match.:------
test_that("computeNormalizationFactors vs normalization",{
expect_true(all(pData(proteinData)$hk_norm_hkFactors ==
as.data.frame(normfactors)$`HK geomean`/exp(mean(log(as.data.frame(normfactors)$`HK geomean`)))))
expect_true(all(pData(proteinData)$neg_norm_negFactors[,1] ==
as.data.frame(normfactors)$`Neg geomean`/exp(mean(log(as.data.frame(normfactors)$`Neg geomean`)))))
expect_equal(as.numeric(dim(normfactors)), as.numeric(c(ncol(proteinData), 2)))
expect_equal(as.numeric(dim(normfactors_area)), as.numeric(c(ncol(proteinData), 3)))
expect_equal(as.numeric(dim(normfactors_area_nuc)), as.numeric(c(ncol(proteinData), 4)))
expect_error(compute_normalization_factors(object = RNAData))
})
test_that("QC plots are plotted", {
expect_error(fig <- plotNormFactorConcordance(object = proteinData, plotFactor = "Segment_Type",
normfactors = normfactors), NA)
expect_true(class(fig)[1] == "gg")
expect_error(fig, NA)
expect_error(fig <- qcProteinSignal(object = proteinData,
neg.names = igg.names), NA)
expect_true(class(fig) == "function")
expect_error(fig(), NA)
proteinOrder <- qcProteinSignalNames(object = proteinData,
neg.names = igg.names)
expect_true(all(proteinOrder %in% rownames(proteinData)))
expect_true(all(rownames(proteinData) %in% proteinOrder))
expect_error(qcProteinSignal(object = RNAData))
})