tests/testthat/test_scRNAseq-methods.R
In ilyessr/conclus: ScRNA-seq Workflow CONCLUS - From CONsensus CLUSters To A Meaningful CONCLUSion
## Data
outputDirectory <- tempdir()
if(!file.exists(outputDirectory))
dir.create(outputDirectory, showWarnings=FALSE)
experimentName <- "LightExperience"
coldataPath <- system.file("extdata/colData.tsv", package="conclus")
columnsMetaData <- loadDataOrMatrix(file=coldataPath, type="coldata",
columnID="cell_ID")
## Creation of the count Matrix
countMatrixPath <- file.path(system.file("extdata", package="conclus"),
"countMatrix.tsv")
countMatrix <- loadDataOrMatrix(file=countMatrixPath, type="countMatrix",
ignoreCellNumber=TRUE)
wrongCountMatrix <- matrix(rep("toto", 1000), ncol = 100)
wrongNamesCountMatrix <- matrix(seq(10000), ncol = 100)
wrongColsCountMatrix <- wrongNamesCountMatrix
rownames(wrongColsCountMatrix) <- paste0(rep("id_", 100) , seq(100))
badCountMatrix <- countMatrix[, 1:10]
badCountMatrix[badCountMatrix > 0] <- 1
## Matrix to have 0 gene after genes filtering
badCountMatrix2 <- countMatrix
badCountMatrix2[1,] <- 100
badCountMatrix2[2:20,] <- 0
## Retrieve the clustering to add
clustAddTab <- read.delim(system.file("extdata/clusters_table.tsv",
package="conclus"))
clustAddTabColThree <- cbind(clustAddTab, mock=rep(1, nrow(clustAddTab)))
clustWrongName <- clustAddTab
colnames(clustWrongName) <- c("test", "test")
clustWrongcells <- clustAddTab
clustWrongcells$cells <- paste0("test", clustWrongcells$cells)
## Load expected results
load(file = system.file("extdata/scrLight.Rdat", package="conclus"))
load(file = system.file("extdata/expected_normalizedMatrix.Rdat",
package="conclus"))
## Construction of the object
scr <- singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory)
## Performing the normalization
scrNorm <- normaliseCountMatrix(scr, coldata = columnsMetaData, info=FALSE)
sceNorm <- getSceNorm(scrNorm)
## Performing tSNE
scrTsne <- generateTSNECoordinates(scrNorm, cores=2, perplexities=c(2,3),
PCs =c(4,5,6,7,8,9,10))
tsneList <- getTSNEList(scrTsne)
tsneListWrong <- tsneList
setCoordinates(tsneListWrong[[1]]) <- getCoordinates(tsneList[[1]])[1:10,]
newList <- list(1, 2, 3)
## Running DbScan
scrDbscan <- runDBSCAN(scrTsne, cores=2, epsilon=c(380, 390, 400),
minPoints=c(2,3))
dbscanList <- getDbscanList(scrDbscan)
clusteringList <- lapply(dbscanList, getClustering)
dbscanListWrong <- dbscanList
setClustering(dbscanListWrong[[1]]) <-
as.matrix(getClustering(dbscanList[[1]])[,1:10])
## Running cluster cells internal
scrCCI <- clusterCellsInternal(scrDbscan, clusterNumber=4, deepSplit=4, cores=2,
clusteringMethod="ward.D2")
cci <- getCellsSimilarityMatrix(scrCCI)
scrCCiwrong <- scrCCI
setCellsSimilarityMatrix(scrCCiwrong) <- matrix(data=1, nrow=1, ncol=1,
dimnames=list("c1", "c1"))
wrongCCI <- matrix(ncol=3, nrow=2, data=seq(6))
wrongCCIbis <- matrix(ncol=3, nrow=3, data=seq(9))
rownames(wrongCCIbis) <- c("c1", "c2", "c3")
colnames(wrongCCIbis) <- c("c3", "c1", "c2")
wrongCCIchar <- matrix(rep("toto", 9), ncol=3, nrow=3)
rownames(wrongCCIchar) <- c("c1", "c2", "c3")
colnames(wrongCCIchar) <- c("c1", "c2", "c3")
## Calculate clusters similarity
scrCSM <- calculateClustersSimilarity(scrCCI)
csm <- getClustersSimilarityMatrix(scrCSM)
orderedCLusters <- getClustersSimilarityOrdered(scrCSM)
## Ranking genes
scrS4MG <- rankGenes(scrCSM)
markers <- getMarkerGenesList(scrS4MG)
## Getting marker genes
scrFinal <- retrieveTopClustersMarkers(scrS4MG, removeDuplicates=FALSE)
scrFinalWrong <- scrFinal
setTSNEList(scrFinalWrong) <- list(new("Tsne"))
## Getting genes info
scrInfos <- retrieveGenesInfo(scrFinal, cores=2)
wrongInfo <- data.frame(uniprot_gn_symbol=c("symbol1", "symbol2", "symbol3"),
clusters=c("1", "2", "3"),
external_gene_name=c("gene1", "gene2", "gene2"),
go_id=c("GO1,GO2", "GO1,GO3", "GO1,GO4"),
mgi_description=c("descrip1", "descrip2", "descrip3"),
entrezgene_description=c("descrip1", "descrip2", "descrip3"),
gene_biotype=c("coding", "coding", "coding"),
chromosome_name=c("1", "2", "3"),
Symbol=c("symbol1", "symbol2", "symbol3"),
ensembl_gene_id=c("ENS1","ENS2", "ENS3"),
mgi_id=c("MGI1", "MGI2", "MGI3"), entrezgene_id=c("1", "2", "3"),
uniprot_gn_id=c("ID1", "ID2", "ID2"))
#################### Construction of the object ####################
test_that("scr is created properly", {
expect_identical(getExperimentName(scrLight),
getExperimentName(scr))
expect_identical(getCountMatrix(scrLight), getCountMatrix(scr))
expect_identical(getSpecies(scrLight), getSpecies(scr))
})
test_that("Errors are thrown when creating scr", {
expM <- "'experimentName' slot is empty. Please fill it."
expect_error(singlecellRNAseq(experimentName = "",
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("Experiment name should contain a single string ",
"describing the experiment, 'My experiment' is not ",
"correct.")
expect_error(singlecellRNAseq(experimentName = "My experiment",
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("The count matrix is empty or does not contain ",
"whole numbers. Please check your count matrix.\n")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = wrongCountMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("The name of the lines should be character class. ",
"Please check your count matrix.\n")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = wrongNamesCountMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("The name of the columns should be character class.",
" Please check your count matrix.\n")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = wrongColsCountMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("species should be 'mouse' or 'human'. '' is ",
"currently not supported.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "",
outputDirectory = outputDirectory), regexp = expM)
expM <- "'outputDirectory' slot is empty. Please fill it."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = ""), regexp = expM)
expM <- "'outputDirectory' slot is empty. Please fill it."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = ""), regexp = expM)
expM <- paste0("'outputDirectory' should be a conform folder path:",
"'path dir' is not.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "human",
outputDirectory = "path dir"), regexp = expM)
expM <- "tSNEList is empty. This should be a list of tSNE objects."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = list()), regexp = expM)
expM <- paste0("The elements in TsneList slot don't have the same ",
"number of cells or the same class")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = tsneListWrong), regexp = expM)
expM <- "Coordinates should be a matrix with two columns X and Y."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = list(TsneCluster(name = "test", pc = 30,
perplexity = 4,
coordinates = matrix(seq_len(9),
ncol=3)))), regexp = expM)
expM <- "tSNEList should be a list of Tsne objects."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = newList), regexp = expM)
expM <- paste0("dbscanList is empty. This should be a list of ",
"dbScan objects.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
dbscanlist = list()), regexp = expM)
expM <- paste0("The elements in DbscanList slot don't have the ",
"same number of cells or the same class")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
dbscanlist = dbscanListWrong), regexp = expM)
expM <- "dbscanList should be a list of Dbscan objects."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
dbscanlist = newList), regexp = expM)
expM <- paste0("'cellsSimilarityMatrix' should have column and ",
"row names corresponding to cell names.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
cellSimMat = wrongCCI), regexp = expM)
expM <- paste0("'cellsSimilarityMatrix' should be a square matrix",
" with identical names in rows and columns.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
cellSimMat = wrongCCIbis), regexp = expM)
expM <- paste0("'cellsSimilarityMatrix' should contain only ",
"numeric values.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
cellSimMat = wrongCCIchar), regexp = expM)
expM <- paste0("'clustersSimilarityMatrix' should have column ",
"and row names corresponding to cluster names.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = wrongCCI), regexp = expM)
expM <- paste0("'clustersSimilarityMatrix' should be a square ",
"matrix with identical names in rows and colums.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = wrongCCIbis), regexp = expM)
expM <- paste0("'clustersSimilarityMatrix' should contain only ",
"numeric values.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = wrongCCIchar), regexp = expM)
expM <- paste0("'clustersSimiliratyOrdered' slot should contain ",
"the same clusters as 'clustersSimilarityMatrix'.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = csm,
clustSimOrdered = factor(c(15,16,17))),
regexp = expM)
expM <- paste0("markerGenesList is empty. This should be a list ",
"of dataframe")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
markgenlist = list()), regexp = expM)
expM <- paste0("'markerGenesList' should contain as many ",
"dataframes as clusters found. Number of dataframes :3 ",
"and the number of cluters found is :4.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimOrdered = orderedCLusters,
markgenlist = markers[-1]), regexp = expM)
expM <- paste0("topMarkers should have the same number of ",
"clusters than the number of clusters found. Nb clusters ",
"for markers: 3. Nb of clusters: 4")
expect_error(setTopMarkers(scrFinal) <- data.frame(
geneName= c("gene1", "gene2", "gene3"),
clusters=c(1,2,3)),
expM)
expM <- paste0("The topMarkers data frame should have the ",
"columns 'geneName' and 'clusters'")
expect_error(setTopMarkers(scrFinal) <-
data.frame(geneNam= rep("gene1", 10),
clust=seq_len(10)), expM)
expM <- "topMarkers is empty. This should be a dataframe"
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustMark = data.frame()), expM)
expM <- "genesInfos is empty. This should be a dataframe"
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
genesInf=data.frame()), expM)
expM <- paste0("The genesInfos data frame should have the columns:",
" uniprot_gn_symbol;clusters;go_id;",
"entrezgene_description;gene_biotype;",
"chromosome_name;Symbol;ensembl_gene_id;",
"entrezgene_id;uniprot_gn_id;mgi_description;mgi_id")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
genesInf=data.frame(test="test")), expM)
expM <- paste0("genesInfos should have the same number of clusters",
" than the number of clusters found. Nb clusters for ",
"genesInfos: 3. Nb of clusters: 4")
expect_error(setGenesInfos(scrInfos) <- wrongInfo, expM)
})
########################### Normalization ###################################
test_that("Normalization works properly", {
expect_match(class(sceNorm), class(expectedNormalizedMatrix))
expect_equal(Biobase::exprs(sceNorm),
Biobase::exprs(expectedNormalizedMatrix))
expM <- "'sizes' parameter should be a vector of numeric values."
expect_error(normaliseCountMatrix(scr, sizes="test"), regexp=expM)
expM <- "'rowdata' parameter should be a data frame or be NULL."
expect_error(normaliseCountMatrix(scr, rowdata="test"), regexp=expM)
expM <- "'coldata' parameter should be a data frame or be NULL."
expect_error(normaliseCountMatrix(scr, coldata="test"), regexp=expM)
expM <- "'alreadyCellFiltered' parameter should be a boolean."
expect_error(normaliseCountMatrix(scr, alreadyCellFiltered="test"),
regexp=expM)
expM <- "'runQuickCluster' parameter should be a boolean."
expect_error(normaliseCountMatrix(scr, runQuickCluster="test"),
regexp=expM)
expM <- "'info' parameter should be a boolean."
expect_error(normaliseCountMatrix(scr, info="test"), regexp=expM)
expM <- paste0("species should be 'mouse' or 'human'. ",
"'melanogaster' is currently not supported.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = countMatrix,
outputDirectory = outputDirectory,
species = "melanogaster")),
regexp=expM)
expM <- paste0("None of your cells has at least 100 genes ",
"expressed. Since the filtering keeps only those cells, ",
"nothing will be kept. Please check the count matrix.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix,
outputDirectory = outputDirectory,
species = "mouse")),
regexp=expM)
expM <- paste0("The provided row metadata should contain the same ",
"number of rows than the matrix.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix,
outputDirectory = outputDirectory,
species = "mouse"),
rowdata=data.frame()), regexp=expM)
expM <- paste0("The provided col metadata should contain the ",
"same number of rows than the matrix number of columns.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix,
outputDirectory = outputDirectory,
species = "mouse"),
coldata=data.frame(), info=FALSE), regexp=expM)
expM <- paste0("There are no more genes after filtering. Maybe",
" the count matrix contains only genes which are",
" less than in 10 cells or more than ",
"all-10 cells. Please check the count matrix.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix2,
outputDirectory = outputDirectory,
species = "mouse"),
info=FALSE),
regexp=expM)
})
################################ TSNE #######################################
test_that("Tsne works properly", {
expect_match(class(tsneList), "list")
expect_match(unique(sapply(tsneList, class)), "Tsne")
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'generateTSNECoordinates' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(generateTSNECoordinates(scr), regexp=expM)
expM <- "'randomSeed' parameter should be an integer."
expect_error(generateTSNECoordinates(scrNorm, randomSeed="string"),
regexp=expM)
expM <- "'cores' parameter should be an integer"
expect_error(generateTSNECoordinates(scrNorm, cores="string"),
regexp=expM)
expM <- "'PCs' parameter should be a vector of numeric."
expect_error(generateTSNECoordinates(scrNorm, PCs=c("str1", "str2"),
regexp=expM))
expM <- "'perplexities' parameter should be a vector of numeric."
expect_error(generateTSNECoordinates(scrNorm,
perplexities=c("str1", "str2")),
regexp=expM)
expM <- "'writeOutput' parameter should be a boolean."
expect_error(generateTSNECoordinates(scrNorm, writeOutput="str"),
regexp=expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'generateTSNECoordinates' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(generateTSNECoordinates(scr, cores=2),
regexp=expM)
})
################################# Dbscan #####################################
test_that("Dbscan works properly", {
# Test class of the output
expect_match(class(dbscanList), "list")
# Test the class of the first element
expect_match(class(dbscanList[[1]]), "Dbscan")
# Test the class of the last element
expect_match(class(dbscanList[[length(dbscanList)]]), "Dbscan")
# Test with a empty class scRNAseq
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'runDBSCAN' function doesn't have its 'sceNorm' slot ",
"updated. Please use 'normaliseCountMatrix' on the object ",
"before.")
expect_error(runDBSCAN(scr), regexp=expM)
## Test with incorrect cores
expM <- "'cores' parameter should be an integer"
expect_error(runDBSCAN(scrTsne, cores="1"), regexp=expM)
## Test with incorrect epsilon
expM <- "'epsilon' parameter should be a vector of numeric"
epsVec <- c("str1", "str2")
expect_error(runDBSCAN(scrTsne, epsilon=epsVec, regexp=expM))
## Test with incorrect minPoints
expM <- "'minPoints' parameter should be a vector of numeric"
minPvec <- c("str1", "str2")
expect_error(runDBSCAN(scrTsne,minPoints=minPvec), regexp=expM)
## Test with incorrect writeOutput
expM <- "'writeOutput' parameter should be a boolean"
expect_error(runDBSCAN(scrTsne, writeOutput="str"), regexp=expM)
expM <- paste("The 'scRNAseq' object that you're using with",
"'runDBSCAN' function doesn't have its 'sceNorm'",
"slot updated. Please use 'normaliseCountMatrix'",
"on the object before.")
expect_error(runDBSCAN(scr, cores=2),
regexp=expM)
expM <- paste("The 'scRNAseq' object that you're using with",
"'runDBSCAN' function doesn't have its 'tSNEList'",
"slot updated. Please use 'generateTSNECoordinates'",
"on the object before.")
expect_error(runDBSCAN(scrNorm, cores=2),
regexp=expM)
})
######################### clusterCellsInternal ###############################
test_that("clusterCellsInternal works properly", {
## Test class of the output
expect_equal(class(cci), c("matrix", "array"))
## Test with a empty sceNorm slot
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'clusterCellsInternal' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(clusterCellsInternal(scr), regexp=expM)
## Test with a empty dbscan slot
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'clusterCellsInternal' function doesn't have its ",
"'dbscanList' slot updated. Please use 'runDBSCAN' on the ",
"object before.")
expect_error(clusterCellsInternal(scrNorm), regexp=expM)
## Test with incorrect clusterNumber
expM <- "'clusterNumber' parameter should be a numeric."
expect_error(clusterCellsInternal(scrDbscan, clusterNumber="str1"),
regexp=expM)
## Test with incorrect deepSplit
expM <- "'deepSplit' parameter should be a numeric."
expect_error(clusterCellsInternal(scrDbscan, deepSplit="str1"),
regexp=expM)
## Test with incorrect cores
expM <- "'cores' parameter should be a numeric."
expect_error(clusterCellsInternal(scrDbscan, cores="str1"),
regexp=expM)
## Test with incorrect clusteringMethod
expM <- paste0("'clusteringMethod' should be one of: ward.D; ",
"ward.D2; single; complete; average; mcquitty; median; ",
"centroid")
expect_error(clusterCellsInternal(scrDbscan,
clusteringMethod="str1"), regexp=expM)
})
######################### calculateClustersSimilarity ########################
test_that("calculateClustersSimilarity works properly", {
## Test with incorrect clusteringMethod
expM <- paste0("'clusteringMethod' should be one of: ward.D; ",
"ward.D2; single; complete; average; mcquitty; median; ",
"centroid")
expect_error(calculateClustersSimilarity(scrDbscan,
clusteringMethod="str1"), regexp=expM)
## Test with unnormalized object
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'calculateClustersSimilarity' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix' on",
" the object before.")
expect_error(calculateClustersSimilarity(scr), regexp=expM)
## Test with default normalizeCountMatrix
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'calculateClustersSimilarity' function doesn't have a correct ",
"'sceNorm' slot. This slot should be a 'SingleCellExperiment' ",
"object containing 'clusters' column in its colData. Please check ",
"if you correctly used 'clusterCellsInternal' on the object.")
expect_error(calculateClustersSimilarity(scrDbscan), regexp=expM)
## Test with
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'calculateClustersSimilarity' function doesn't have its ",
"'cellsSimilarityMatrix' slot updated by clusterCellsInternal. ",
"Please use 'clusterCellsInternal' on the object before.")
expect_error(calculateClustersSimilarity(scrCCiwrong), regexp=expM)
})
################################## Plotting ####################################
test_that("plotCellSimilarity work properly", {
## Test with object doesn't have consensus clusters
expM <- paste("You have to calculate the cluster similarity matrix",
"before plotting.")
expect_error(plotCellSimilarity(scr), expM)
## Test with incorrect colorPalette
expM <- paste("The number of clusters is greater than the number of",
"given colors.")
expect_error(plotCellSimilarity(scrFinal, colorPalette="str1" ), expM)
## Test with incorrect statePalette
expM <- paste("The number of clusters is greater than the number of",
"given colors.")
expect_error(plotCellSimilarity(scrFinal, statePalette="str1" ), expM)
## Test with incorrect orderClusters
expM <- "orderClusters should be a boolean."
expect_error(plotCellSimilarity(scrFinal, orderClusters="str1" ), expM)
## Test with incorrect savePlot
expM <- "savePlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, savePlot="str1" ), expM)
## Test with incorrect plotPDF
expM <- "plotPDF should be a boolean."
expect_error(plotCellSimilarity(scrFinal, plotPDF="str1" ), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, returnPlot="str1" ), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotCellSimilarity(scrFinal, width="str1" ), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotCellSimilarity(scrFinal, height="str1" ), expM)
## Test with incorrect onefile
expM <- "onefile should be a boolean."
expect_error(plotCellSimilarity(scrFinal, onefile="str1" ), expM)
## Test with incorrect showRowNames
expM <- "showRowNames should be a boolean."
expect_error(plotCellSimilarity(scrFinal, showRowNames="str1" ), expM)
## Test with incorrect showColnames
expM <-"showColnames should be a boolean."
expect_error(plotCellSimilarity(scrFinal, showColnames="str1" ), expM)
## Test with incorrect fontsize
expM <- "fontsize should be a numeric."
expect_error(plotCellSimilarity(scrFinal, fontsize="str1" ), expM)
## Test with incorrect fontsizeRow
expM <- "fontsizeRow should be a numeric."
expect_error(plotCellSimilarity(scrFinal, fontsizeRow="str1" ), expM)
## Test with incorrect widthPNG
expM <- "widthPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, widthPNG="str1" ), expM)
## Test with incorrect heightPNG
expM <- "heightPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, heightPNG="str1" ), expM)
expM <- "silentPlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotCellSimilarity(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
})
test_that("plotClusteredTSNE work properly", {
expM <- "columnName should be: clusters, noColor, or state."
expect_error(plotClusteredTSNE(scrFinal, columnName="toto"), expM)
expM <- paste0("The number of elements of TSNEList is not equal ",
"to PCs x perplexities. Contact the developper.")
expect_error(plotClusteredTSNE(scrFinalWrong), expM)
## Test with no consensus clusters
expM <- paste0("You have to calculate the cluster similarity matrix",
" before plotting.")
expect_error(plotClusteredTSNE(scr), expM)
## Test with incorrect colorPalette
expM <- paste0("The number of clusters is greater than the number of",
" given colors.")
expect_error(plotClusteredTSNE(scrFinal, colorPalette="str1" ), expM)
## Test with incorrect PCs
expM <- "'PCs' parameter should be a vector of numeric."
expect_error(plotClusteredTSNE(scrFinal, PCs=c("str1", "str2"), expM))
## Test with incorrect perplexities
expM <- "'perplexities' parameter should be a vector of numeric."
expect_error(plotClusteredTSNE(scrFinal, perplexities=c("str1", "str2")),
regexp=expM)
## Test with incorrect columnName
expM <- "columnName should be: clusters, noColor, or state."
expect_error(plotClusteredTSNE(scrFinal, columnName="toto"), expM)
expM <- paste("The number of elements of TSNEList is not equal",
"to PCs x perplexities. Contact the developper.")
expect_error(plotClusteredTSNE(scrFinalWrong), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, returnPlot="str1" ), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, width="str1" ), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, height="str1" ), expM)
## Test with incorrect onefile
expM <- "onefile should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, onefile="str1" ), expM)
expM <- "savePlot should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, savePlot="str1" ), expM)
expM <- "plotPDF should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, plotPDF="str1" ), expM)
expM <- "widthPNG should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, widthPNG="str1" ), expM)
expM <- "heightPNG should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, heightPNG="str1" ), expM)
expM <- "silentPlot should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotClusteredTSNE(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
expM <- "tSNENb should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, tSNENb="str1"), expM)
expM <- "The chosen tSNENb should be smaller than PCs x perplexities."
expect_error(plotClusteredTSNE(scrFinal, tSNENb=99), expM)
})
test_that("plotCellHeatmap work properly", {
## Test with object doesn't have consensus clusters
expM <- paste("You have to calculate the cluster markers before plotting.",
"Please see retrieveTopClustersMarkers() method.")
expect_error(plotCellHeatmap(scr), expM)
## Test with incorrect fileName
expM <- "fileName should be a string, no path."
expect_error(plotCellHeatmap(scrFinal, fileName=TRUE), expM)
expect_error(plotCellHeatmap(scrFinal, fileName="dir/file"), expM)
## Test with incorrect meanCentered
expM <- "meanCentered should be a boolean."
expect_error(plotCellHeatmap(scrFinal, meanCentered="str2"), expM)
## Test with incorrect orderClusters
expM <- "orderClusters should be a boolean."
expect_error(plotCellHeatmap(scrFinal, fileName="str1",
orderClusters="str2"), expM)
## Test with incorrect orderGenes
expM <- "orderGenes should be a boolean."
expect_error(plotCellHeatmap(scrFinal, fileName="str1",
orderGenes="str2"), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotCellHeatmap(scrFinal, returnPlot="str2"), expM)
## Test with incorrect saveHeatmapTable
expM <- "savePlot should be a boolean."
expect_error(plotCellHeatmap(scrFinal, savePlot="str2"), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotCellHeatmap(scrFinal, width="str2"), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotCellHeatmap(scrFinal, height="str2"), expM)
expM <- "onefile should be a boolean."
expect_error(plotCellHeatmap(scrFinal, onefile="str2"), expM)
expM <- "clusterCols should be a boolean."
expect_error(plotCellHeatmap(scrFinal, clusterCols="str2"), expM)
expM <- "showColnames should be a boolean."
expect_error(plotCellHeatmap(scrFinal, showColnames="str2"), expM)
expM <- "plotPDF should be a boolean."
expect_error(plotCellHeatmap(scrFinal, plotPDF="str2"), expM)
expM <- "fontsize should be a numeric."
expect_error(plotCellHeatmap(scrFinal, fontsize="str2"), expM)
expM <- "fontsizeRow should be a numeric."
expect_error(plotCellHeatmap(scrFinal, fontsizeRow="str2"), expM)
expM <- "widthPNG should be a numeric."
expect_error(plotCellHeatmap(scrFinal, widthPNG="str2"), expM)
expM <- "heightPNG should be a numeric."
expect_error(plotCellHeatmap(scrFinal, heightPNG="str2"), expM)
expM <- "silentPlot should be a boolean."
expect_error(plotCellHeatmap(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotCellHeatmap(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
})
test_that("plotGeneExpression work properly", {
## Correct gene name
geneName <- as.character(getTopMarkers(scrFinal)[1,1])
## Test that the queried gene is in the expression matrix
expM <- "Gene is not found in expression matrix."
expect_error(plotGeneExpression(scrFinal, geneName="gene1"), expM)
## Verify that the TSNE coordinates are correct
expM <- paste0("The row names of the tSNE coordinates matrix should be ",
"equal to the colnames of the expression matrix.")
expect_error(plotGeneExpression(scrNorm, geneName=geneName), expM)
## Test with incorrect geneName
expM <- paste("geneName should be a marker founded by ",
"retrieveTopClustersMarkers method'. Please see the",
"documentation about retrieveTopClustersMarkers method.")
expect_error(plotGeneExpression(scrCSM, geneName=geneName), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
returnPlot = "str1"), expM)
## Test with incorrect savePlot
expM <- "savePlot should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName = geneName,
savePlot="str1"), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotGeneExpression(scrFinal, geneName = geneName,
width = "str1"), expM)
## Test with incorrect height
expM <- "height should be a numeric."
geneName <- as.character(getTopMarkers(scrFinal)[1,1])
expect_error(plotGeneExpression(scrFinal, geneName = geneName,
height = "str1"), expM)
## Test with incorrect silentPlot
expM <- "silentPlot should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
silentPlot="str1"), expM)
## Test with incorrect plotPDF
expM <- "plotPDF should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
plotPDF="str1"), expM)
## Test when nothing is output
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
silentPlot=TRUE, savePlot=FALSE, returnPlot=FALSE), expM)
})
test_that("plotClustersSimilarity work properly", {
## Test with object doesn't have consensus clusters
expM <- paste0("You have to calculate the cluster similarity matrix",
" before plotting.")
expect_error(plotClustersSimilarity(scr), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotClustersSimilarity(scrFinal, returnPlot="str1" ), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotClustersSimilarity(scrFinal, width="str1" ), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotClustersSimilarity(scrFinal, height="str1" ), expM)
## Test with incorrect onefile
expM <- "onefile should be a boolean."
expect_error(plotClustersSimilarity(scrFinal, onefile="str1" ), expM)
## Test with incorrect fontsize
expM <- "fontsize should be a numeric."
expect_error(plotCellSimilarity(scrFinal, fontsize="str1" ), expM)
## Test with incorrect savePlot
expM <- "savePlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, savePlot="str1"))
## Test with incorrect plotPDF
expM <- "plotPDF should be a boolean."
expect_error(plotCellSimilarity(scrFinal, plotPDF="str1"))
## Test with incorrect widthPNG
expM <- "widthPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, widthPNG="str1"))
## Test with incorrect heightPNG
expM <- "heightPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, heightPNG="str1"))
expM <- "silentPlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotCellSimilarity(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
})
################################ markers ###################################
test_that("rankGenes method works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'rankGenes' function doesn't have its 'SceNorm' slot ",
"updated. Please use 'normaliseCountMatrix' on the object",
" before.")
expect_error(rankGenes(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'rankGenes' function doesn't have a correct 'SceNorm' ",
"slot. This slot should be a 'SingleCellExperiment' object",
" containing 'clusters' column in its colData. Please ",
"check if you correctly used 'clusterCellsInternal' on the",
" object.")
expect_error(rankGenes(scrDbscan), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'rankGenes' function doesn't have its ",
"'clustersSimilarityMatrix' slot updated. Please use ",
"'clusterCellsInternal' on the object before.")
expect_error(rankGenes(scrCCiwrong), expM)
})
test_that("retrieveGenesInfo method works properly", {
expM <- "orderGenes should be 'initial' or 'alphabetical'."
expect_error(retrieveGenesInfo(scr, orderGenes="test"), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' function doesn't have its 'SceNorm' ",
"slot updated. Please use 'normaliseCountMatrix' on the ",
"object before.")
expect_error(retrieveGenesInfo(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' function doesn't have a correct ",
"'SceNorm' slot. This slot should be a ",
"'SingleCellExperiment' object containing 'clusters' ",
"column in its colData. Please check if you correctly used",
" 'clusterCellsInternal' on the object.")
expect_error(retrieveGenesInfo(scrDbscan), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' function doesn't have a similarity ",
"matrix, Please use 'calculateClustersSimilarity' on the ",
"object before.")
expect_error(retrieveGenesInfo(scrCCI), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' does not have marker genes. Please ",
"use 'retrieveTopClustersMarkers' before.")
expect_error(retrieveGenesInfo(scrCSM), expM)
expect_error(retrieveGenesInfo(scrS4MG), expM)
expM <- "saveInfos should be a boolean."
expect_error(retrieveGenesInfo(scrFinal, saveInfos="str1"))
})
test_that("retrieveTopClustersMarkers method works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveTopClustersMarkers' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(retrieveTopClustersMarkers(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveTopClustersMarkers' function doesn't have a ",
"correct 'sceNorm' slot. This slot should be a ",
"'SingleCellExperiment' object containing 'clusters' ",
"column in its colData. Please check if you correctly ",
"used 'clusterCellsInternal' on the object.")
expect_error(retrieveTopClustersMarkers(scrNorm), expM)
expect_error(retrieveTopClustersMarkers(scrTsne), expM)
expect_error(retrieveTopClustersMarkers(scrDbscan),expM)
expM <- paste0("Something wrong with number of clusters. It is ",
"supposed to be equal to : 4. Current number: 1. Did you",
" use 'calculateClustersSimilarity' and 'rankGenes'?")
expect_error(retrieveTopClustersMarkers(scrCCI), expM)
expect_error(retrieveTopClustersMarkers(scrCSM), expM)
})
################################## ExportResults ##############################
test_that("exportResults works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' method doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(exportResults(scr, saveNormalizedMatrix=TRUE), expM)
expect_error(exportResults(scr,saveRowData=TRUE),expM)
expect_error(exportResults(scr,saveColData=TRUE),expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' method doesn't have its 'tSNEList' slot ",
"updated. Please use 'generateTSNECoordinates' on the ",
"object before.")
expect_error(exportResults(scrNorm, saveTsne=TRUE),expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' method doesn't have its 'dbscanList' slot",
" updated. Please use 'runDBSCAN' on the object before.")
expect_error(exportResults(scrTsne, saveDBScan=TRUE),expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'cellsSimilarityMatrix' slot updated. Please use ",
"'clusterCellsInternal' on the object before.")
expect_error(exportResults(scrDbscan,
saveCellsSimilarityMatrix=TRUE), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'clustersSimilarityMatrix' slot updated. Please use ",
"'calculateClustersSimilarity' on the object before.")
expect_error(exportResults(scrCCI,
saveClustersSimilarityMatrix=TRUE), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its columns ",
"metadata updated. Please use ",
"'calculateClustersSimilarity' on the object before.")
expect_error(exportResults(scrCCI), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'markerGenesList' slot updated. Please use 'rankGenes' ",
"on the object before.")
expect_error(exportResults(scrCSM, saveClusteringResults=FALSE,
saveFullMarkers=TRUE), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'clustersMarkers' slot updated. Please use ",
"'retrieveTopClustersMarkers' on the object before")
expect_error(exportResults(scrS4MG, saveClusteringResults=FALSE,
saveTopMarkers=TRUE), expM)
})
################################## testClustering ###########################
test_that("testClustering works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'testClustering' method doesn't have its 'sceNorm' slot ",
"updated. Please use 'normaliseCountMatrix' on the object",
" before.")
expect_error(testClustering(scr), expM)
expM <- "'dbscanEpsilon' parameter should be an integer."
expect_error(testClustering(scrNorm, dbscanEpsilon="test"),
expM)
expM <- "'minPts' parameter should be an integer"
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts="test"), expM)
expM <- paste0("'perplexities' parameter should be a vector of ",
"numeric.")
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts=5, perplexities="test"), expM)
expM <- "'PCs' parameter should be a vector of numeric."
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts=5, perplexities=30, PCs="test"), expM)
expM <- "'randomSeed' parameter should be an integer."
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts=5, perplexities=30, PCs=4,
randomSeed="test"), expM)
expM <- paste0("dbscanEpsilon, minPts, perplexities, PCs, and ",
"randomSeed should be a single value.")
expect_error(testClustering(scrNorm, dbscanEpsilon=c(1,21)), expM)
})
####################### retrieveTableClustersCells ###########################
test_that("retrieveTableClustersCells works properly",{
expM <- paste0("clusterCellsInternal should be performed before ",
"retrieving this information.")
expect_error(retrieveTableClustersCells(scr), expM)
})
############################ addClustering ###########################
test_that("addClustering works properly",{
expM <- "Either filePathAdd or clustToAdd should be given."
expect_error(addClustering(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its columns ",
"metadata updated. Please use ",
"'calculateClustersSimilarity' on the object before.")
expect_error(addClustering(scr, clusToAdd=clustAddTab), expM)
expM <- paste0("The file given to filePathAdd should contain ",
"two columns 'clusters' and 'cells'. Instead it con")
expect_error(addClustering(scrInfos, clusToAdd=clustAddTabColThree),
expM)
expM <- paste0("The file given to filePathAdd should contain two",
" columns 'clusters' and 'cells'. Instead it contains: ",
"clusters-cells-mock")
expect_error(addClustering(scrInfos,
clusToAdd=clustAddTabColThree), expM)
expM <- paste0("The file given to filePathAdd should contain two ",
"columns 'clusters' and 'cells' Instead it contains: ",
"test-test")
expect_error(addClustering(scrInfos,
clusToAdd=clustWrongName), expM)
expM <- paste0("The cells column in theObject clustering results ",
"contains cells names that are not the same then the ones ",
"of the cluster to add. Make sure that the cells names of ",
"the cluster to add are the same.")
expect_error(addClustering(scrInfos,
clusToAdd=clustWrongcells), expM)
})
ilyessr/conclus documentation built on April 8, 2022, 1:43 p.m.
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## Data
outputDirectory <- tempdir()
if(!file.exists(outputDirectory))
dir.create(outputDirectory, showWarnings=FALSE)
experimentName <- "LightExperience"
coldataPath <- system.file("extdata/colData.tsv", package="conclus")
columnsMetaData <- loadDataOrMatrix(file=coldataPath, type="coldata",
columnID="cell_ID")
## Creation of the count Matrix
countMatrixPath <- file.path(system.file("extdata", package="conclus"),
"countMatrix.tsv")
countMatrix <- loadDataOrMatrix(file=countMatrixPath, type="countMatrix",
ignoreCellNumber=TRUE)
wrongCountMatrix <- matrix(rep("toto", 1000), ncol = 100)
wrongNamesCountMatrix <- matrix(seq(10000), ncol = 100)
wrongColsCountMatrix <- wrongNamesCountMatrix
rownames(wrongColsCountMatrix) <- paste0(rep("id_", 100) , seq(100))
badCountMatrix <- countMatrix[, 1:10]
badCountMatrix[badCountMatrix > 0] <- 1
## Matrix to have 0 gene after genes filtering
badCountMatrix2 <- countMatrix
badCountMatrix2[1,] <- 100
badCountMatrix2[2:20,] <- 0
## Retrieve the clustering to add
clustAddTab <- read.delim(system.file("extdata/clusters_table.tsv",
package="conclus"))
clustAddTabColThree <- cbind(clustAddTab, mock=rep(1, nrow(clustAddTab)))
clustWrongName <- clustAddTab
colnames(clustWrongName) <- c("test", "test")
clustWrongcells <- clustAddTab
clustWrongcells$cells <- paste0("test", clustWrongcells$cells)
## Load expected results
load(file = system.file("extdata/scrLight.Rdat", package="conclus"))
load(file = system.file("extdata/expected_normalizedMatrix.Rdat",
package="conclus"))
## Construction of the object
scr <- singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory)
## Performing the normalization
scrNorm <- normaliseCountMatrix(scr, coldata = columnsMetaData, info=FALSE)
sceNorm <- getSceNorm(scrNorm)
## Performing tSNE
scrTsne <- generateTSNECoordinates(scrNorm, cores=2, perplexities=c(2,3),
PCs =c(4,5,6,7,8,9,10))
tsneList <- getTSNEList(scrTsne)
tsneListWrong <- tsneList
setCoordinates(tsneListWrong[[1]]) <- getCoordinates(tsneList[[1]])[1:10,]
newList <- list(1, 2, 3)
## Running DbScan
scrDbscan <- runDBSCAN(scrTsne, cores=2, epsilon=c(380, 390, 400),
minPoints=c(2,3))
dbscanList <- getDbscanList(scrDbscan)
clusteringList <- lapply(dbscanList, getClustering)
dbscanListWrong <- dbscanList
setClustering(dbscanListWrong[[1]]) <-
as.matrix(getClustering(dbscanList[[1]])[,1:10])
## Running cluster cells internal
scrCCI <- clusterCellsInternal(scrDbscan, clusterNumber=4, deepSplit=4, cores=2,
clusteringMethod="ward.D2")
cci <- getCellsSimilarityMatrix(scrCCI)
scrCCiwrong <- scrCCI
setCellsSimilarityMatrix(scrCCiwrong) <- matrix(data=1, nrow=1, ncol=1,
dimnames=list("c1", "c1"))
wrongCCI <- matrix(ncol=3, nrow=2, data=seq(6))
wrongCCIbis <- matrix(ncol=3, nrow=3, data=seq(9))
rownames(wrongCCIbis) <- c("c1", "c2", "c3")
colnames(wrongCCIbis) <- c("c3", "c1", "c2")
wrongCCIchar <- matrix(rep("toto", 9), ncol=3, nrow=3)
rownames(wrongCCIchar) <- c("c1", "c2", "c3")
colnames(wrongCCIchar) <- c("c1", "c2", "c3")
## Calculate clusters similarity
scrCSM <- calculateClustersSimilarity(scrCCI)
csm <- getClustersSimilarityMatrix(scrCSM)
orderedCLusters <- getClustersSimilarityOrdered(scrCSM)
## Ranking genes
scrS4MG <- rankGenes(scrCSM)
markers <- getMarkerGenesList(scrS4MG)
## Getting marker genes
scrFinal <- retrieveTopClustersMarkers(scrS4MG, removeDuplicates=FALSE)
scrFinalWrong <- scrFinal
setTSNEList(scrFinalWrong) <- list(new("Tsne"))
## Getting genes info
scrInfos <- retrieveGenesInfo(scrFinal, cores=2)
wrongInfo <- data.frame(uniprot_gn_symbol=c("symbol1", "symbol2", "symbol3"),
clusters=c("1", "2", "3"),
external_gene_name=c("gene1", "gene2", "gene2"),
go_id=c("GO1,GO2", "GO1,GO3", "GO1,GO4"),
mgi_description=c("descrip1", "descrip2", "descrip3"),
entrezgene_description=c("descrip1", "descrip2", "descrip3"),
gene_biotype=c("coding", "coding", "coding"),
chromosome_name=c("1", "2", "3"),
Symbol=c("symbol1", "symbol2", "symbol3"),
ensembl_gene_id=c("ENS1","ENS2", "ENS3"),
mgi_id=c("MGI1", "MGI2", "MGI3"), entrezgene_id=c("1", "2", "3"),
uniprot_gn_id=c("ID1", "ID2", "ID2"))
#################### Construction of the object ####################
test_that("scr is created properly", {
expect_identical(getExperimentName(scrLight),
getExperimentName(scr))
expect_identical(getCountMatrix(scrLight), getCountMatrix(scr))
expect_identical(getSpecies(scrLight), getSpecies(scr))
})
test_that("Errors are thrown when creating scr", {
expM <- "'experimentName' slot is empty. Please fill it."
expect_error(singlecellRNAseq(experimentName = "",
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("Experiment name should contain a single string ",
"describing the experiment, 'My experiment' is not ",
"correct.")
expect_error(singlecellRNAseq(experimentName = "My experiment",
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("The count matrix is empty or does not contain ",
"whole numbers. Please check your count matrix.\n")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = wrongCountMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("The name of the lines should be character class. ",
"Please check your count matrix.\n")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = wrongNamesCountMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("The name of the columns should be character class.",
" Please check your count matrix.\n")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = wrongColsCountMatrix,
species = "mouse",
outputDirectory = outputDirectory), regexp = expM)
expM <- paste0("species should be 'mouse' or 'human'. '' is ",
"currently not supported.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "",
outputDirectory = outputDirectory), regexp = expM)
expM <- "'outputDirectory' slot is empty. Please fill it."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = ""), regexp = expM)
expM <- "'outputDirectory' slot is empty. Please fill it."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = ""), regexp = expM)
expM <- paste0("'outputDirectory' should be a conform folder path:",
"'path dir' is not.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "human",
outputDirectory = "path dir"), regexp = expM)
expM <- "tSNEList is empty. This should be a list of tSNE objects."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = list()), regexp = expM)
expM <- paste0("The elements in TsneList slot don't have the same ",
"number of cells or the same class")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = tsneListWrong), regexp = expM)
expM <- "Coordinates should be a matrix with two columns X and Y."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = list(TsneCluster(name = "test", pc = 30,
perplexity = 4,
coordinates = matrix(seq_len(9),
ncol=3)))), regexp = expM)
expM <- "tSNEList should be a list of Tsne objects."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
tSNElist = newList), regexp = expM)
expM <- paste0("dbscanList is empty. This should be a list of ",
"dbScan objects.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
dbscanlist = list()), regexp = expM)
expM <- paste0("The elements in DbscanList slot don't have the ",
"same number of cells or the same class")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
dbscanlist = dbscanListWrong), regexp = expM)
expM <- "dbscanList should be a list of Dbscan objects."
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
dbscanlist = newList), regexp = expM)
expM <- paste0("'cellsSimilarityMatrix' should have column and ",
"row names corresponding to cell names.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
cellSimMat = wrongCCI), regexp = expM)
expM <- paste0("'cellsSimilarityMatrix' should be a square matrix",
" with identical names in rows and columns.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
cellSimMat = wrongCCIbis), regexp = expM)
expM <- paste0("'cellsSimilarityMatrix' should contain only ",
"numeric values.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
cellSimMat = wrongCCIchar), regexp = expM)
expM <- paste0("'clustersSimilarityMatrix' should have column ",
"and row names corresponding to cluster names.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = wrongCCI), regexp = expM)
expM <- paste0("'clustersSimilarityMatrix' should be a square ",
"matrix with identical names in rows and colums.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = wrongCCIbis), regexp = expM)
expM <- paste0("'clustersSimilarityMatrix' should contain only ",
"numeric values.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = wrongCCIchar), regexp = expM)
expM <- paste0("'clustersSimiliratyOrdered' slot should contain ",
"the same clusters as 'clustersSimilarityMatrix'.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimMat = csm,
clustSimOrdered = factor(c(15,16,17))),
regexp = expM)
expM <- paste0("markerGenesList is empty. This should be a list ",
"of dataframe")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
markgenlist = list()), regexp = expM)
expM <- paste0("'markerGenesList' should contain as many ",
"dataframes as clusters found. Number of dataframes :3 ",
"and the number of cluters found is :4.")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustSimOrdered = orderedCLusters,
markgenlist = markers[-1]), regexp = expM)
expM <- paste0("topMarkers should have the same number of ",
"clusters than the number of clusters found. Nb clusters ",
"for markers: 3. Nb of clusters: 4")
expect_error(setTopMarkers(scrFinal) <- data.frame(
geneName= c("gene1", "gene2", "gene3"),
clusters=c(1,2,3)),
expM)
expM <- paste0("The topMarkers data frame should have the ",
"columns 'geneName' and 'clusters'")
expect_error(setTopMarkers(scrFinal) <-
data.frame(geneNam= rep("gene1", 10),
clust=seq_len(10)), expM)
expM <- "topMarkers is empty. This should be a dataframe"
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
clustMark = data.frame()), expM)
expM <- "genesInfos is empty. This should be a dataframe"
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
genesInf=data.frame()), expM)
expM <- paste0("The genesInfos data frame should have the columns:",
" uniprot_gn_symbol;clusters;go_id;",
"entrezgene_description;gene_biotype;",
"chromosome_name;Symbol;ensembl_gene_id;",
"entrezgene_id;uniprot_gn_id;mgi_description;mgi_id")
expect_error(singlecellRNAseq(experimentName = experimentName,
countMatrix = countMatrix,
species = "mouse",
outputDirectory = outputDirectory,
genesInf=data.frame(test="test")), expM)
expM <- paste0("genesInfos should have the same number of clusters",
" than the number of clusters found. Nb clusters for ",
"genesInfos: 3. Nb of clusters: 4")
expect_error(setGenesInfos(scrInfos) <- wrongInfo, expM)
})
########################### Normalization ###################################
test_that("Normalization works properly", {
expect_match(class(sceNorm), class(expectedNormalizedMatrix))
expect_equal(Biobase::exprs(sceNorm),
Biobase::exprs(expectedNormalizedMatrix))
expM <- "'sizes' parameter should be a vector of numeric values."
expect_error(normaliseCountMatrix(scr, sizes="test"), regexp=expM)
expM <- "'rowdata' parameter should be a data frame or be NULL."
expect_error(normaliseCountMatrix(scr, rowdata="test"), regexp=expM)
expM <- "'coldata' parameter should be a data frame or be NULL."
expect_error(normaliseCountMatrix(scr, coldata="test"), regexp=expM)
expM <- "'alreadyCellFiltered' parameter should be a boolean."
expect_error(normaliseCountMatrix(scr, alreadyCellFiltered="test"),
regexp=expM)
expM <- "'runQuickCluster' parameter should be a boolean."
expect_error(normaliseCountMatrix(scr, runQuickCluster="test"),
regexp=expM)
expM <- "'info' parameter should be a boolean."
expect_error(normaliseCountMatrix(scr, info="test"), regexp=expM)
expM <- paste0("species should be 'mouse' or 'human'. ",
"'melanogaster' is currently not supported.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = countMatrix,
outputDirectory = outputDirectory,
species = "melanogaster")),
regexp=expM)
expM <- paste0("None of your cells has at least 100 genes ",
"expressed. Since the filtering keeps only those cells, ",
"nothing will be kept. Please check the count matrix.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix,
outputDirectory = outputDirectory,
species = "mouse")),
regexp=expM)
expM <- paste0("The provided row metadata should contain the same ",
"number of rows than the matrix.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix,
outputDirectory = outputDirectory,
species = "mouse"),
rowdata=data.frame()), regexp=expM)
expM <- paste0("The provided col metadata should contain the ",
"same number of rows than the matrix number of columns.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix,
outputDirectory = outputDirectory,
species = "mouse"),
coldata=data.frame(), info=FALSE), regexp=expM)
expM <- paste0("There are no more genes after filtering. Maybe",
" the count matrix contains only genes which are",
" less than in 10 cells or more than ",
"all-10 cells. Please check the count matrix.")
expect_error(normaliseCountMatrix(singlecellRNAseq(
experimentName = experimentName,
countMatrix = badCountMatrix2,
outputDirectory = outputDirectory,
species = "mouse"),
info=FALSE),
regexp=expM)
})
################################ TSNE #######################################
test_that("Tsne works properly", {
expect_match(class(tsneList), "list")
expect_match(unique(sapply(tsneList, class)), "Tsne")
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'generateTSNECoordinates' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(generateTSNECoordinates(scr), regexp=expM)
expM <- "'randomSeed' parameter should be an integer."
expect_error(generateTSNECoordinates(scrNorm, randomSeed="string"),
regexp=expM)
expM <- "'cores' parameter should be an integer"
expect_error(generateTSNECoordinates(scrNorm, cores="string"),
regexp=expM)
expM <- "'PCs' parameter should be a vector of numeric."
expect_error(generateTSNECoordinates(scrNorm, PCs=c("str1", "str2"),
regexp=expM))
expM <- "'perplexities' parameter should be a vector of numeric."
expect_error(generateTSNECoordinates(scrNorm,
perplexities=c("str1", "str2")),
regexp=expM)
expM <- "'writeOutput' parameter should be a boolean."
expect_error(generateTSNECoordinates(scrNorm, writeOutput="str"),
regexp=expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'generateTSNECoordinates' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(generateTSNECoordinates(scr, cores=2),
regexp=expM)
})
################################# Dbscan #####################################
test_that("Dbscan works properly", {
# Test class of the output
expect_match(class(dbscanList), "list")
# Test the class of the first element
expect_match(class(dbscanList[[1]]), "Dbscan")
# Test the class of the last element
expect_match(class(dbscanList[[length(dbscanList)]]), "Dbscan")
# Test with a empty class scRNAseq
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'runDBSCAN' function doesn't have its 'sceNorm' slot ",
"updated. Please use 'normaliseCountMatrix' on the object ",
"before.")
expect_error(runDBSCAN(scr), regexp=expM)
## Test with incorrect cores
expM <- "'cores' parameter should be an integer"
expect_error(runDBSCAN(scrTsne, cores="1"), regexp=expM)
## Test with incorrect epsilon
expM <- "'epsilon' parameter should be a vector of numeric"
epsVec <- c("str1", "str2")
expect_error(runDBSCAN(scrTsne, epsilon=epsVec, regexp=expM))
## Test with incorrect minPoints
expM <- "'minPoints' parameter should be a vector of numeric"
minPvec <- c("str1", "str2")
expect_error(runDBSCAN(scrTsne,minPoints=minPvec), regexp=expM)
## Test with incorrect writeOutput
expM <- "'writeOutput' parameter should be a boolean"
expect_error(runDBSCAN(scrTsne, writeOutput="str"), regexp=expM)
expM <- paste("The 'scRNAseq' object that you're using with",
"'runDBSCAN' function doesn't have its 'sceNorm'",
"slot updated. Please use 'normaliseCountMatrix'",
"on the object before.")
expect_error(runDBSCAN(scr, cores=2),
regexp=expM)
expM <- paste("The 'scRNAseq' object that you're using with",
"'runDBSCAN' function doesn't have its 'tSNEList'",
"slot updated. Please use 'generateTSNECoordinates'",
"on the object before.")
expect_error(runDBSCAN(scrNorm, cores=2),
regexp=expM)
})
######################### clusterCellsInternal ###############################
test_that("clusterCellsInternal works properly", {
## Test class of the output
expect_equal(class(cci), c("matrix", "array"))
## Test with a empty sceNorm slot
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'clusterCellsInternal' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(clusterCellsInternal(scr), regexp=expM)
## Test with a empty dbscan slot
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'clusterCellsInternal' function doesn't have its ",
"'dbscanList' slot updated. Please use 'runDBSCAN' on the ",
"object before.")
expect_error(clusterCellsInternal(scrNorm), regexp=expM)
## Test with incorrect clusterNumber
expM <- "'clusterNumber' parameter should be a numeric."
expect_error(clusterCellsInternal(scrDbscan, clusterNumber="str1"),
regexp=expM)
## Test with incorrect deepSplit
expM <- "'deepSplit' parameter should be a numeric."
expect_error(clusterCellsInternal(scrDbscan, deepSplit="str1"),
regexp=expM)
## Test with incorrect cores
expM <- "'cores' parameter should be a numeric."
expect_error(clusterCellsInternal(scrDbscan, cores="str1"),
regexp=expM)
## Test with incorrect clusteringMethod
expM <- paste0("'clusteringMethod' should be one of: ward.D; ",
"ward.D2; single; complete; average; mcquitty; median; ",
"centroid")
expect_error(clusterCellsInternal(scrDbscan,
clusteringMethod="str1"), regexp=expM)
})
######################### calculateClustersSimilarity ########################
test_that("calculateClustersSimilarity works properly", {
## Test with incorrect clusteringMethod
expM <- paste0("'clusteringMethod' should be one of: ward.D; ",
"ward.D2; single; complete; average; mcquitty; median; ",
"centroid")
expect_error(calculateClustersSimilarity(scrDbscan,
clusteringMethod="str1"), regexp=expM)
## Test with unnormalized object
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'calculateClustersSimilarity' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix' on",
" the object before.")
expect_error(calculateClustersSimilarity(scr), regexp=expM)
## Test with default normalizeCountMatrix
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'calculateClustersSimilarity' function doesn't have a correct ",
"'sceNorm' slot. This slot should be a 'SingleCellExperiment' ",
"object containing 'clusters' column in its colData. Please check ",
"if you correctly used 'clusterCellsInternal' on the object.")
expect_error(calculateClustersSimilarity(scrDbscan), regexp=expM)
## Test with
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'calculateClustersSimilarity' function doesn't have its ",
"'cellsSimilarityMatrix' slot updated by clusterCellsInternal. ",
"Please use 'clusterCellsInternal' on the object before.")
expect_error(calculateClustersSimilarity(scrCCiwrong), regexp=expM)
})
################################## Plotting ####################################
test_that("plotCellSimilarity work properly", {
## Test with object doesn't have consensus clusters
expM <- paste("You have to calculate the cluster similarity matrix",
"before plotting.")
expect_error(plotCellSimilarity(scr), expM)
## Test with incorrect colorPalette
expM <- paste("The number of clusters is greater than the number of",
"given colors.")
expect_error(plotCellSimilarity(scrFinal, colorPalette="str1" ), expM)
## Test with incorrect statePalette
expM <- paste("The number of clusters is greater than the number of",
"given colors.")
expect_error(plotCellSimilarity(scrFinal, statePalette="str1" ), expM)
## Test with incorrect orderClusters
expM <- "orderClusters should be a boolean."
expect_error(plotCellSimilarity(scrFinal, orderClusters="str1" ), expM)
## Test with incorrect savePlot
expM <- "savePlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, savePlot="str1" ), expM)
## Test with incorrect plotPDF
expM <- "plotPDF should be a boolean."
expect_error(plotCellSimilarity(scrFinal, plotPDF="str1" ), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, returnPlot="str1" ), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotCellSimilarity(scrFinal, width="str1" ), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotCellSimilarity(scrFinal, height="str1" ), expM)
## Test with incorrect onefile
expM <- "onefile should be a boolean."
expect_error(plotCellSimilarity(scrFinal, onefile="str1" ), expM)
## Test with incorrect showRowNames
expM <- "showRowNames should be a boolean."
expect_error(plotCellSimilarity(scrFinal, showRowNames="str1" ), expM)
## Test with incorrect showColnames
expM <-"showColnames should be a boolean."
expect_error(plotCellSimilarity(scrFinal, showColnames="str1" ), expM)
## Test with incorrect fontsize
expM <- "fontsize should be a numeric."
expect_error(plotCellSimilarity(scrFinal, fontsize="str1" ), expM)
## Test with incorrect fontsizeRow
expM <- "fontsizeRow should be a numeric."
expect_error(plotCellSimilarity(scrFinal, fontsizeRow="str1" ), expM)
## Test with incorrect widthPNG
expM <- "widthPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, widthPNG="str1" ), expM)
## Test with incorrect heightPNG
expM <- "heightPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, heightPNG="str1" ), expM)
expM <- "silentPlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotCellSimilarity(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
})
test_that("plotClusteredTSNE work properly", {
expM <- "columnName should be: clusters, noColor, or state."
expect_error(plotClusteredTSNE(scrFinal, columnName="toto"), expM)
expM <- paste0("The number of elements of TSNEList is not equal ",
"to PCs x perplexities. Contact the developper.")
expect_error(plotClusteredTSNE(scrFinalWrong), expM)
## Test with no consensus clusters
expM <- paste0("You have to calculate the cluster similarity matrix",
" before plotting.")
expect_error(plotClusteredTSNE(scr), expM)
## Test with incorrect colorPalette
expM <- paste0("The number of clusters is greater than the number of",
" given colors.")
expect_error(plotClusteredTSNE(scrFinal, colorPalette="str1" ), expM)
## Test with incorrect PCs
expM <- "'PCs' parameter should be a vector of numeric."
expect_error(plotClusteredTSNE(scrFinal, PCs=c("str1", "str2"), expM))
## Test with incorrect perplexities
expM <- "'perplexities' parameter should be a vector of numeric."
expect_error(plotClusteredTSNE(scrFinal, perplexities=c("str1", "str2")),
regexp=expM)
## Test with incorrect columnName
expM <- "columnName should be: clusters, noColor, or state."
expect_error(plotClusteredTSNE(scrFinal, columnName="toto"), expM)
expM <- paste("The number of elements of TSNEList is not equal",
"to PCs x perplexities. Contact the developper.")
expect_error(plotClusteredTSNE(scrFinalWrong), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, returnPlot="str1" ), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, width="str1" ), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, height="str1" ), expM)
## Test with incorrect onefile
expM <- "onefile should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, onefile="str1" ), expM)
expM <- "savePlot should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, savePlot="str1" ), expM)
expM <- "plotPDF should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, plotPDF="str1" ), expM)
expM <- "widthPNG should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, widthPNG="str1" ), expM)
expM <- "heightPNG should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, heightPNG="str1" ), expM)
expM <- "silentPlot should be a boolean."
expect_error(plotClusteredTSNE(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotClusteredTSNE(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
expM <- "tSNENb should be a numeric."
expect_error(plotClusteredTSNE(scrFinal, tSNENb="str1"), expM)
expM <- "The chosen tSNENb should be smaller than PCs x perplexities."
expect_error(plotClusteredTSNE(scrFinal, tSNENb=99), expM)
})
test_that("plotCellHeatmap work properly", {
## Test with object doesn't have consensus clusters
expM <- paste("You have to calculate the cluster markers before plotting.",
"Please see retrieveTopClustersMarkers() method.")
expect_error(plotCellHeatmap(scr), expM)
## Test with incorrect fileName
expM <- "fileName should be a string, no path."
expect_error(plotCellHeatmap(scrFinal, fileName=TRUE), expM)
expect_error(plotCellHeatmap(scrFinal, fileName="dir/file"), expM)
## Test with incorrect meanCentered
expM <- "meanCentered should be a boolean."
expect_error(plotCellHeatmap(scrFinal, meanCentered="str2"), expM)
## Test with incorrect orderClusters
expM <- "orderClusters should be a boolean."
expect_error(plotCellHeatmap(scrFinal, fileName="str1",
orderClusters="str2"), expM)
## Test with incorrect orderGenes
expM <- "orderGenes should be a boolean."
expect_error(plotCellHeatmap(scrFinal, fileName="str1",
orderGenes="str2"), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotCellHeatmap(scrFinal, returnPlot="str2"), expM)
## Test with incorrect saveHeatmapTable
expM <- "savePlot should be a boolean."
expect_error(plotCellHeatmap(scrFinal, savePlot="str2"), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotCellHeatmap(scrFinal, width="str2"), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotCellHeatmap(scrFinal, height="str2"), expM)
expM <- "onefile should be a boolean."
expect_error(plotCellHeatmap(scrFinal, onefile="str2"), expM)
expM <- "clusterCols should be a boolean."
expect_error(plotCellHeatmap(scrFinal, clusterCols="str2"), expM)
expM <- "showColnames should be a boolean."
expect_error(plotCellHeatmap(scrFinal, showColnames="str2"), expM)
expM <- "plotPDF should be a boolean."
expect_error(plotCellHeatmap(scrFinal, plotPDF="str2"), expM)
expM <- "fontsize should be a numeric."
expect_error(plotCellHeatmap(scrFinal, fontsize="str2"), expM)
expM <- "fontsizeRow should be a numeric."
expect_error(plotCellHeatmap(scrFinal, fontsizeRow="str2"), expM)
expM <- "widthPNG should be a numeric."
expect_error(plotCellHeatmap(scrFinal, widthPNG="str2"), expM)
expM <- "heightPNG should be a numeric."
expect_error(plotCellHeatmap(scrFinal, heightPNG="str2"), expM)
expM <- "silentPlot should be a boolean."
expect_error(plotCellHeatmap(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotCellHeatmap(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
})
test_that("plotGeneExpression work properly", {
## Correct gene name
geneName <- as.character(getTopMarkers(scrFinal)[1,1])
## Test that the queried gene is in the expression matrix
expM <- "Gene is not found in expression matrix."
expect_error(plotGeneExpression(scrFinal, geneName="gene1"), expM)
## Verify that the TSNE coordinates are correct
expM <- paste0("The row names of the tSNE coordinates matrix should be ",
"equal to the colnames of the expression matrix.")
expect_error(plotGeneExpression(scrNorm, geneName=geneName), expM)
## Test with incorrect geneName
expM <- paste("geneName should be a marker founded by ",
"retrieveTopClustersMarkers method'. Please see the",
"documentation about retrieveTopClustersMarkers method.")
expect_error(plotGeneExpression(scrCSM, geneName=geneName), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
returnPlot = "str1"), expM)
## Test with incorrect savePlot
expM <- "savePlot should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName = geneName,
savePlot="str1"), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotGeneExpression(scrFinal, geneName = geneName,
width = "str1"), expM)
## Test with incorrect height
expM <- "height should be a numeric."
geneName <- as.character(getTopMarkers(scrFinal)[1,1])
expect_error(plotGeneExpression(scrFinal, geneName = geneName,
height = "str1"), expM)
## Test with incorrect silentPlot
expM <- "silentPlot should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
silentPlot="str1"), expM)
## Test with incorrect plotPDF
expM <- "plotPDF should be a boolean."
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
plotPDF="str1"), expM)
## Test when nothing is output
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotGeneExpression(scrFinal, geneName=geneName,
silentPlot=TRUE, savePlot=FALSE, returnPlot=FALSE), expM)
})
test_that("plotClustersSimilarity work properly", {
## Test with object doesn't have consensus clusters
expM <- paste0("You have to calculate the cluster similarity matrix",
" before plotting.")
expect_error(plotClustersSimilarity(scr), expM)
## Test with incorrect returnPlot
expM <- "returnPlot should be a boolean."
expect_error(plotClustersSimilarity(scrFinal, returnPlot="str1" ), expM)
## Test with incorrect width
expM <- "width should be a numeric."
expect_error(plotClustersSimilarity(scrFinal, width="str1" ), expM)
## Test with incorrect height
expM <- "height should be a numeric."
expect_error(plotClustersSimilarity(scrFinal, height="str1" ), expM)
## Test with incorrect onefile
expM <- "onefile should be a boolean."
expect_error(plotClustersSimilarity(scrFinal, onefile="str1" ), expM)
## Test with incorrect fontsize
expM <- "fontsize should be a numeric."
expect_error(plotCellSimilarity(scrFinal, fontsize="str1" ), expM)
## Test with incorrect savePlot
expM <- "savePlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, savePlot="str1"))
## Test with incorrect plotPDF
expM <- "plotPDF should be a boolean."
expect_error(plotCellSimilarity(scrFinal, plotPDF="str1"))
## Test with incorrect widthPNG
expM <- "widthPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, widthPNG="str1"))
## Test with incorrect heightPNG
expM <- "heightPNG should be a numeric."
expect_error(plotCellSimilarity(scrFinal, heightPNG="str1"))
expM <- "silentPlot should be a boolean."
expect_error(plotCellSimilarity(scrFinal, silentPlot="str1" ), expM)
expM <- paste0("You do not plot, neither save the heatmap or return the ",
"object. Nothing will happen. You should either plot the results, ",
"return the object or save the heatmap.")
expect_error(plotCellSimilarity(scrFinal, silentPlot=TRUE, savePlot=FALSE,
returnPlot=FALSE), expM)
})
################################ markers ###################################
test_that("rankGenes method works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'rankGenes' function doesn't have its 'SceNorm' slot ",
"updated. Please use 'normaliseCountMatrix' on the object",
" before.")
expect_error(rankGenes(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'rankGenes' function doesn't have a correct 'SceNorm' ",
"slot. This slot should be a 'SingleCellExperiment' object",
" containing 'clusters' column in its colData. Please ",
"check if you correctly used 'clusterCellsInternal' on the",
" object.")
expect_error(rankGenes(scrDbscan), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'rankGenes' function doesn't have its ",
"'clustersSimilarityMatrix' slot updated. Please use ",
"'clusterCellsInternal' on the object before.")
expect_error(rankGenes(scrCCiwrong), expM)
})
test_that("retrieveGenesInfo method works properly", {
expM <- "orderGenes should be 'initial' or 'alphabetical'."
expect_error(retrieveGenesInfo(scr, orderGenes="test"), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' function doesn't have its 'SceNorm' ",
"slot updated. Please use 'normaliseCountMatrix' on the ",
"object before.")
expect_error(retrieveGenesInfo(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' function doesn't have a correct ",
"'SceNorm' slot. This slot should be a ",
"'SingleCellExperiment' object containing 'clusters' ",
"column in its colData. Please check if you correctly used",
" 'clusterCellsInternal' on the object.")
expect_error(retrieveGenesInfo(scrDbscan), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' function doesn't have a similarity ",
"matrix, Please use 'calculateClustersSimilarity' on the ",
"object before.")
expect_error(retrieveGenesInfo(scrCCI), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveGenesInfo' does not have marker genes. Please ",
"use 'retrieveTopClustersMarkers' before.")
expect_error(retrieveGenesInfo(scrCSM), expM)
expect_error(retrieveGenesInfo(scrS4MG), expM)
expM <- "saveInfos should be a boolean."
expect_error(retrieveGenesInfo(scrFinal, saveInfos="str1"))
})
test_that("retrieveTopClustersMarkers method works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveTopClustersMarkers' function doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(retrieveTopClustersMarkers(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'retrieveTopClustersMarkers' function doesn't have a ",
"correct 'sceNorm' slot. This slot should be a ",
"'SingleCellExperiment' object containing 'clusters' ",
"column in its colData. Please check if you correctly ",
"used 'clusterCellsInternal' on the object.")
expect_error(retrieveTopClustersMarkers(scrNorm), expM)
expect_error(retrieveTopClustersMarkers(scrTsne), expM)
expect_error(retrieveTopClustersMarkers(scrDbscan),expM)
expM <- paste0("Something wrong with number of clusters. It is ",
"supposed to be equal to : 4. Current number: 1. Did you",
" use 'calculateClustersSimilarity' and 'rankGenes'?")
expect_error(retrieveTopClustersMarkers(scrCCI), expM)
expect_error(retrieveTopClustersMarkers(scrCSM), expM)
})
################################## ExportResults ##############################
test_that("exportResults works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' method doesn't have its ",
"'sceNorm' slot updated. Please use 'normaliseCountMatrix'",
" on the object before.")
expect_error(exportResults(scr, saveNormalizedMatrix=TRUE), expM)
expect_error(exportResults(scr,saveRowData=TRUE),expM)
expect_error(exportResults(scr,saveColData=TRUE),expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' method doesn't have its 'tSNEList' slot ",
"updated. Please use 'generateTSNECoordinates' on the ",
"object before.")
expect_error(exportResults(scrNorm, saveTsne=TRUE),expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' method doesn't have its 'dbscanList' slot",
" updated. Please use 'runDBSCAN' on the object before.")
expect_error(exportResults(scrTsne, saveDBScan=TRUE),expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'cellsSimilarityMatrix' slot updated. Please use ",
"'clusterCellsInternal' on the object before.")
expect_error(exportResults(scrDbscan,
saveCellsSimilarityMatrix=TRUE), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'clustersSimilarityMatrix' slot updated. Please use ",
"'calculateClustersSimilarity' on the object before.")
expect_error(exportResults(scrCCI,
saveClustersSimilarityMatrix=TRUE), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its columns ",
"metadata updated. Please use ",
"'calculateClustersSimilarity' on the object before.")
expect_error(exportResults(scrCCI), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'markerGenesList' slot updated. Please use 'rankGenes' ",
"on the object before.")
expect_error(exportResults(scrCSM, saveClusteringResults=FALSE,
saveFullMarkers=TRUE), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its ",
"'clustersMarkers' slot updated. Please use ",
"'retrieveTopClustersMarkers' on the object before")
expect_error(exportResults(scrS4MG, saveClusteringResults=FALSE,
saveTopMarkers=TRUE), expM)
})
################################## testClustering ###########################
test_that("testClustering works properly", {
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'testClustering' method doesn't have its 'sceNorm' slot ",
"updated. Please use 'normaliseCountMatrix' on the object",
" before.")
expect_error(testClustering(scr), expM)
expM <- "'dbscanEpsilon' parameter should be an integer."
expect_error(testClustering(scrNorm, dbscanEpsilon="test"),
expM)
expM <- "'minPts' parameter should be an integer"
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts="test"), expM)
expM <- paste0("'perplexities' parameter should be a vector of ",
"numeric.")
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts=5, perplexities="test"), expM)
expM <- "'PCs' parameter should be a vector of numeric."
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts=5, perplexities=30, PCs="test"), expM)
expM <- "'randomSeed' parameter should be an integer."
expect_error(testClustering(scrNorm, dbscanEpsilon=1.4,
minPts=5, perplexities=30, PCs=4,
randomSeed="test"), expM)
expM <- paste0("dbscanEpsilon, minPts, perplexities, PCs, and ",
"randomSeed should be a single value.")
expect_error(testClustering(scrNorm, dbscanEpsilon=c(1,21)), expM)
})
####################### retrieveTableClustersCells ###########################
test_that("retrieveTableClustersCells works properly",{
expM <- paste0("clusterCellsInternal should be performed before ",
"retrieving this information.")
expect_error(retrieveTableClustersCells(scr), expM)
})
############################ addClustering ###########################
test_that("addClustering works properly",{
expM <- "Either filePathAdd or clustToAdd should be given."
expect_error(addClustering(scr), expM)
expM <- paste0("The 'scRNAseq' object that you're using with ",
"'exportResults' function doesn't have its columns ",
"metadata updated. Please use ",
"'calculateClustersSimilarity' on the object before.")
expect_error(addClustering(scr, clusToAdd=clustAddTab), expM)
expM <- paste0("The file given to filePathAdd should contain ",
"two columns 'clusters' and 'cells'. Instead it con")
expect_error(addClustering(scrInfos, clusToAdd=clustAddTabColThree),
expM)
expM <- paste0("The file given to filePathAdd should contain two",
" columns 'clusters' and 'cells'. Instead it contains: ",
"clusters-cells-mock")
expect_error(addClustering(scrInfos,
clusToAdd=clustAddTabColThree), expM)
expM <- paste0("The file given to filePathAdd should contain two ",
"columns 'clusters' and 'cells' Instead it contains: ",
"test-test")
expect_error(addClustering(scrInfos,
clusToAdd=clustWrongName), expM)
expM <- paste0("The cells column in theObject clustering results ",
"contains cells names that are not the same then the ones ",
"of the cluster to add. Make sure that the cells names of ",
"the cluster to add are the same.")
expect_error(addClustering(scrInfos,
clusToAdd=clustWrongcells), expM)
})
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