tests/testthat/test-clusterMany.R
In epurdom/clusterExperiment: Compare Clusterings for Single-Cell Sequencing
context("clusterMany")
test_that("`clusterMany` works with matrix, list of data, ClusterExperiment objects, and
SummarizedExperiments", {
#check all builtin methods
expect_silent(clustNothing <- clusterMany(mat,
ks=c(3,4),clusterFunction=listBuiltInFunctions(),
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE, makeMissingDiss=TRUE))
expect_silent(clustDF <- clusterMany(data.frame(mat),
ks=c(3,4),clusterFunction=listBuiltInFunctions(),
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE, makeMissingDiss=TRUE))
expect_is(clustNothing, "ClusterExperiment")
expect_is(clustNothing, "SingleCellExperiment")
expect_is(clustNothing, "SummarizedExperiment")
expect_silent(clustNothing2 <- clusterMany(se, ks=c(3,4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_equal(colData(clustNothing2),colData(se))
expect_equal(rownames(clustNothing2),rownames(se))
expect_equal(colnames(clustNothing2),colnames(se))
expect_equal(metadata(clustNothing2),metadata(se))
expect_equal(rowData(clustNothing2),rowData(se))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing))
expect_true(all(clusterTypes(clustNothing)=="clusterMany"))
#test running on ClusterExperiment Object -- should add the new clustering
expect_silent(clustNothing3 <- clusterMany(ccSE,
ks=c(3,4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE, verbose=FALSE))
expect_true(nClusterings(clustNothing3) == nClusterings(ccSE) + 2)
expect_equal(colData(clustNothing3),colData(ccSE))
expect_equal(rownames(clustNothing3),rownames(ccSE))
expect_equal(colnames(clustNothing3),colnames(ccSE))
expect_equal(metadata(clustNothing3),metadata(ccSE))
expect_equal(rowData(clustNothing3),rowData(ccSE))
expect_silent(test <- clusterSingle(se, subsample=FALSE,
sequential=FALSE,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=4)),
isCount=FALSE))
expect_silent(clustNothing3<- clusterMany(test,
ks=c(3,4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE, verbose=FALSE))
expect_silent(clustNothing4<- clusterMany(clustNothing3,
ks=c(3:4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, eraseOld=TRUE))
expect_equal(clustNothing3,clustNothing4)
expect_silent(clustNothing5<- clusterMany(clustNothing3,
ks=c(5:6),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, eraseOld=FALSE))
expect_equal(NCOL(clusterMatrix(clustNothing5)),5)
expect_silent(ppIndex<-workflowClusterDetails(clustNothing5))
expect_equal(as.numeric(table(ppIndex[,"iteration"])),c(2,2))
})
test_that("`clusterMany` works with SingleCellExperiment", {
#check with sce that has dimRed:
#takes a while with all functions, but sometimes turn up surprises.
#for some reason if do clusterFunction=listBuiltInFunctions(),
# expect_silent gets warning, but not if run myself.
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction=listBuiltInFunctions()[[kk]],
makeMissingDiss=TRUE,
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE))
}
expect_equal(colData(clustNothing2),colData(sceSimDataDimRed))
expect_equal(rownames(clustNothing2),rownames(sceSimDataDimRed))
expect_equal(colnames(clustNothing2),colnames(sceSimDataDimRed))
expect_equal(metadata(clustNothing2),metadata(sceSimDataDimRed))
expect_equal(rowData(clustNothing2),rowData(sceSimDataDimRed))
expect_equal(reducedDims(clustNothing2),reducedDims(sceSimDataDimRed))
})
# # FIXME: need to make this operational
# test_that("`clusterMany` matches `clusterSingle` results", {
#
# subArgs<-list(clusterFunction="kmeans",classifyMethod="All")
# expect_message(ce<-clusterMany(smSimSE,
# isCount = FALSE,
# ks = 4:5,
# alphas=c(0.1),
# reduceMethod="PCA",
# nReducedDims=10,
# minSizes=1,
# subsample=TRUE,
# sequential=TRUE,
# clusterFunction="hierarchical01",
# subsampleArgs=subArgs,
# makeMissingDiss=TRUE, verbose=FALSE,
# random.seed=176201),"Not all of the methods requested in 'reduceMethod' have been calculated")
#
# mainArgs<-list( clusterFunction="hierarchical01",minSize=1,
# clusterArgs=list(alpha=0.1))
# seqArgs<-list(k0=4,beta=0.9)
# set.seed(176201)
# expect_silent(ce1<-clusterSingle(smSimSE,
# isCount = FALSE,
# saveSubsamplingMatrix=TRUE,
# reduceMethod="PCA",
# nDims=10,
# subsample=TRUE,
# sequential=TRUE,
# mainClusterArgs=mainArgs,
# subsampleArgs=subArgs,
# seqArgs=seqArgs,
# makeMissingDiss=TRUE
# ))
# expect_equal(primaryCluster(ce),primaryCluster(ce1))
#
# })
test_that("`clusterMany` works with reduceMethod a reducedDims",{
#check picking all dims in single reduceMethod same as apply directly to matrix
expect_silent(clustNothing <-
clusterMany(t(reducedDims(sceSimDataDimRed)[["PCA"]]),
ks=c(3,4),clusterFunction="pam",
reduceMethod="none",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam",
reduceMethod="PCA",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
expect_equal(NCOL(clusterMatrix(clustNothing)),2)
expect_equal(NCOL(clusterMatrix(clustNothing3)),2)
expect_equal(NCOL(clusterMatrix(clustNothing3)),2)
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
# check picking certain dims in single
# reduceMethod same as apply directly to matrix
# and that get right reducedDim returned
expect_silent(clustNothing <-
clusterMany(simData,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="PCA",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(NCOL(clusterMatrix(clustNothing)),4)
expect_equal(abs(reducedDim(clustNothing,"PCA")),
abs(reducedDim(sceSimDataDimRed,"PCA")[,1:6]))
expect_silent(clustNothing2 <-
clusterMany(sceSimDataDimRed,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="PCA",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(NCOL(clusterMatrix(clustNothing2)),4)
expect_equal(reducedDim(clustNothing2,"PCA"),
reducedDim(sceSimDataDimRed,"PCA"))
expect_message(clustNothing4 <-
clusterMany(sceSimData,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="PCA", clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(clusterMatrix(clustNothing2),
clusterMatrix(clustNothing4))
expect_message(clustNothingBoth1<-
clusterMany(clustNothing4,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod=c("PCA","mad"),
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, verbose=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated")
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages( clustNothingBoth2<-
clusterMany(clustNothingBoth1,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod=c("PCA","mad"),
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, verbose=FALSE)
)
)
expect_equal(clusterMatrix(clustNothingBoth1,
which="clusterMany"), clusterMatrix(clustNothingBoth2,
which="clusterMany"))
#check picking reduceMethod="none" same as apply directly to matrix
expect_silent(clustNothing <-
clusterMany(simData, ks=c(3,4),
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(sceSimDataDimRed, ks=c(3,4),
clusterFunction="pam", reduceMethod="none",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
#checks that nReducedDims ignored if reduceMethod="none"
expect_silent(clustNothing <-
clusterMany(simData,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="none",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,
verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(sceSimDataDimRed,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="none",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
})
test_that("`clusterMany` works with reduceMethod a filtering",{
expect_message(clustNothing4 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam", reduceMethod="mad",
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_error(clustNothing5 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam", reduceMethod=c("mad","cv"),
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE),"do not match any stored or built-in filtering statistics or dimensionality reduction")
expect_message(clustNothing5 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam", reduceMethod=c("mad","abscv"),
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_true(all(filterNames(sceSimDataDimRed) %in% filterNames(clustNothing5)))
expect_true(all(c("mad","abscv","var","mean") %in% filterNames(clustNothing5)))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(clusterMany(clustNothing5,
ks=c(3,4),clusterFunction="pam", reduceMethod=c("mad","abscv"),
subsample=FALSE, sequential=FALSE, verbose=FALSE)
)
)
})
test_that("`clusterMany` works with hdf5", {
# These are slow!
skip_on_os("windows")
skip_on_os("mac")
########
#Check if use PCA (not in hdf5) changes nothing, as expect.
########
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <- clusterMany(hdfSCE,
ks=c(3,4),clusterFunction=listBuiltInFunctions()[[kk]],
makeMissingDiss=TRUE,
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
}
expect_silent(clustNothing <-
clusterMany(t(reducedDims(sceSimDataDimRed)[["PCA"]]),
ks=c(3,4),clusterFunction="pam",
reduceMethod="none",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(hdfSCE,
ks=c(3,4),clusterFunction="pam",
reduceMethod="PCA", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
expect_equal(NCOL(clusterMatrix(clustNothing)),2)
expect_equal(NCOL(clusterMatrix(clustNothing3)),2)
########
#Check if not using PCA (reduceMethod = "none")
########
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <-
clusterMany(hdfSCE,reduceMethod = "none",
ks=c(3,4), makeMissingDiss=TRUE,
clusterFunction=listBuiltInFunctions()[[kk]],
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
}
########
#Check directly on hdf5 object
########
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <-
clusterMany(assay(hdfObj),reduceMethod = "none",
ks=c(3,4),clusterFunction=listBuiltInFunctions()[[kk]],
subsample=FALSE, sequential=FALSE,
makeMissingDiss=TRUE,
isCount=FALSE,verbose=FALSE))
}
})
test_that("`clusterMany` works changing parameters", {
# These are slow!
skip_on_os("windows")
skip_on_os("mac")
#--------
#check dim reduce in combination
#--------
expect_silent(cc <- clusterMany(mat,
ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var","abscv","mad"),
clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
verbose=FALSE, isCount=FALSE))
expect_equal(sort(reducedDimNames(cc)),sort(c("PCA")))
expect_equal(sort(filterNames(cc)),sort(c("var","abscv","mean","mad")))
expect_message(cc2 <- clusterMany(se,
ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var","abscv","mad"),
clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
verbose=FALSE, isCount=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(sort(reducedDimNames(cc2)),sort(c("PCA")))
expect_equal(sort(filterNames(cc2)),
sort(c("b","var","abscv","mean","mad")))
expect_message(cc3 <- clusterMany(sce, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var","abscv","mad"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(sort(reducedDimNames(cc3)),sort(c("PCA")))
expect_equal(sort(filterNames(cc3)),sort(c("b","var","abscv","mean","mad")))
#Only existing values
expect_silent(cc4 <- clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none","Red1","Filter1","Filter2"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_equal(sort(reducedDimNames(cc4)),sort(c("Red1")))
expect_equal(sort(filterNames(cc4)),sort(c("b","Filter1","Filter2")))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages( ceReRun <- clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none","Red1","Filter1","Filter2"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE)
)
)
expect_equal(sort(reducedDimNames(ceReRun)),sort(reducedDimNames(cc4)))
expect_equal(sort(filterNames(ceReRun)),sort(filterNames(cc4)))
#Only existing values
expect_silent(cc4 <- clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none","Red1","Filter1","Filter2"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_equal(sort(reducedDimNames(cc4)),sort(c("Red1")))
expect_equal(sort(filterNames(cc4)),sort(c("b","Filter1","Filter2")))
#--------
# Mixing saved and unsaved (gives warnings/errors)
#--------
#following gives warning because can't mix saved and calculate internally
notAllWarning<-"All values of 'reduceMethod' need to either match an existing"
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),notAllWarning)
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),notAllWarning)
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),notAllWarning)
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),
notAllWarning)
#repeat for ce
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),notAllWarning)
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),notAllWarning)
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),notAllWarning)
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),
notAllWarning)
#--------
# Mixing mix across filter/reduceMethod okay
#--------
sceSimData2<-sceFull
reducedDims(sceSimData2)<-SimpleList()
expect_message(c1<-clusterMany(sceSimData2, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(clusterExperiment:::filterStats(c1),clusterExperiment:::filterStats(sceSimData2))
expect_equal(reducedDimNames(c1),"PCA")
sceSimData3<-sceFull
rowData(sceSimData3)<-NULL
expect_message(c2<-clusterMany(sceSimData3, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(reducedDims(c2),reducedDims(sceSimData3))
expect_equal(filterNames(c2),"var")
#repeat for ce
ce5<-cc4
reducedDims(ce5)<-SimpleList()
expect_message(c1<-clusterMany(ce5, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(clusterExperiment:::filterStats(c1),clusterExperiment:::filterStats(ce5))
expect_equal(reducedDimNames(c1),"PCA")
ce6<-cc4
rowData(ce6)<-NULL
expect_message(c2<-clusterMany(ce6, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(reducedDims(c2),reducedDims(ce6))
expect_equal(filterNames(c2),"var")
#--------
#check if only dim reduction
#--------
expect_silent(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
sceFull2<-makeReducedDims(sceFull,reducedDims="PCA",maxDims=10,isCount=FALSE)
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10),nReducedDims=c(2),
reduceMethod=c("PCA","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10),nReducedDims=c(2),
reduceMethod=c("Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
#--------
#check only filter
#--------
expect_silent(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
sceFull2<-makeFilterStats(sceFull,filterStat="var",isCount=FALSE)
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
#--------
#check only none
#--------
expect_silent(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
#--------
#check returning paramMatrix
#--------
expect_silent(param <- clusterMany(mat,
ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),reduceMethod=c("none","PCA","var"),
clusterFunction="pam", subsample=FALSE, sequential=FALSE,run=FALSE,verbose=FALSE,
isCount=FALSE))
# #check that giving param$paramMatrix works -- not implemented...
# cc2 <- clusterMany(mat, ks=c(3,4),nFilterDims=c(10, 15),nReducedDims=c(3,4),
# reduceMethod=c("none","PCA","var"),clusterFunction="pam",
# subsample=FALSE, sequential=FALSE,verbose=FALSE,
# isCount=FALSE,paramMatrix=param$paramMatrix, mainClusterArgs=param$mainClusterArgs,
# seqArgs=param$seqArgs,subsampleArgs=param$subsampleArgs)
# expect_equal(cc,cc2)
expect_silent(cc2 <- clusterMany(mat, ks=c(3,4),clusterFunction="pam",
distFunction=c("euclidean","manhattan",NA),
subsample=FALSE, sequential=FALSE,verbose=FALSE,
isCount=FALSE, makeMissingDiss=TRUE))
# # #check giving distance -- this still doesn't work.
# # #problem to just give dist because need to grab from global environment
# # # So doesn't work in testthat
# dist1<-function(x){dist(x,method="manhattan")}
# dist2<-function(x){dist(x)}
# expect_silent(cc <- clusterMany(mat, ks=c(3,4),clusterFunction="pam",
# distFunction=c("dist1","dist2",NA),
# subsample=FALSE, sequential=FALSE,verbose=FALSE,
# isCount=FALSE))
# expect_equal(unname(clusterMatrix(cc)),unname(clusterMatrix(cc2)))
#
#check doesn't spit out warnings because alphas/mainClustering args not match
expect_silent(clusterMany(mat,
clusterFunction=c("pam","hierarchical01"),
ks=c(3,4),
alphas=c(0.1,0.2),
subsample=FALSE, sequential=FALSE,
verbose=FALSE, makeMissingDiss=TRUE,
mainClusterArgs=list(clusterArgs=list(evalClusterMethod="average")),
isCount=FALSE))
#check doesn't spit out warnings because alphas/mainClustering args not match
expect_silent(clusterMany(mat,
clusterFunction=c("pam","hierarchical01"),ks=c(3,4),
betas=c(.7,.9), minSizes=c(3,5),
subsample=FALSE, makeMissingDiss=TRUE, sequential=FALSE,verbose=FALSE,
mainClusterArgs=list(clusterArgs=list(evalClusterMethod="average")),
isCount=FALSE))
})
test_that("`getClusterManyParams` works", {
expect_silent(cc<-clusterMany(mat, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,run=TRUE,verbose=FALSE,
isCount=FALSE))
expect_silent(cc<-makeConsensus(cc,proportion=1,whichClusters = "clusterMany"))
expect_silent(paramAll<-getClusterManyParams(cc))
expect_equal(sort(colnames(paramAll)),sort(c("clusteringIndex", "reduceMethod", "nReducedDims", "nFilterDims", "k")))
expect_true(is.data.frame(paramAll))
expect_equal(sort(as.character(unique(paramAll[,"reduceMethod"]))),sort(c("none","var","PCA")))
expect_equal(sort(unique(paramAll[,"nReducedDims"]),na.last=TRUE),sort(c(NA,3,4),na.last=TRUE))
expect_equal(sort(unique(paramAll[,"nFilterDims"]),na.last=TRUE),sort(c(NA,10,15),na.last=TRUE))
expect_true(is.numeric(paramAll[,"k"]))
# check simplify=TRUE
expect_silent(paramSub<-getClusterManyParams(cc,whichClusters=c(4,6),
simplify=TRUE))
expect_equal(sort(colnames(paramSub)),sort(c("clusteringIndex", "reduceMethod","nFilterDims")))
expect_true(is.data.frame(paramSub))
expect_equal(sort(unique(paramSub[,"nFilterDims"]),na.last=TRUE),c(10,NA))
expect_warning(getClusterManyParams(cc,whichClusters=1:5),"some clusters indicated in 'whichClusters' do not have type 'clusterMany'")
expect_warning(getClusterManyParams(cc,whichClusters=1),"did not return any clusters of type 'clusterMany'")
expect_warning(getClusterManyParams(cc,whichClusters="mergeClusters"),"did not return any clusters")
})
test_that("`clusterMany` consistent results (no transformation)", {
#----
#check get the same result from previous times when transform the data
#Relies on having these checks in clusterSingle, so know clusterSingle is right
#----
#make it big enough can do pca and filter...
contData<-simData[,1:20]
expectTrans1<-round(contData[1,],2)
expect_silent(testSE<-SummarizedExperiment(contData))
expect_silent(testSCE<-as(testSE,"SingleCellExperiment"))
#matrix
expect_silent(ccVar<-clusterSingle(contData,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_silent(ccPCA<-clusterSingle(contData,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_silent(ccNone<-clusterSingle(contData,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_silent(cm<-clusterMany(contData, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=FALSE))
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SE
expect_silent(ccVar<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE)
)
)
expect_silent(ccNone<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_message(cm<-clusterMany(testSE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE, verbose=FALSE,
reduceMethod=c("PCA","var","none"),
nReducedDims=3, nFilterDims=3,isCount=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SCE
expect_silent(ccVar<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE)
)
)
expect_silent(ccNone<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_message(cm<-clusterMany(testSCE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"),verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#CE
expect_silent(ccVar2<-clusterSingle(ccVar,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccPCA2<-clusterSingle(ccPCA,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccNone2<-clusterSingle(ccNone,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(cm2<-clusterMany(cm, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3)
)
)
expect_equal(nClusterings(cm2),6)
expect_silent(params<-getClusterManyParams(cm2))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm2)[1,],2), expectTrans1)
})
test_that("`clusterMany` consistent results (with transformation)", {
#----
#check get the same result from previous times when transform the data
#Relies on tests in clusterSingle being right
#----
#make it big enough can do pca and filter...
countData<-simCount[,1:20]
expect_silent(testSE<-SummarizedExperiment(countData))
expect_silent(testSCE<-as(testSE,"SingleCellExperiment"))
expectTrans1<-round(log2(countData[1,]+1),2)
#matrix
expect_silent(ccVar<-clusterSingle(countData,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_silent(ccPCA<-clusterSingle(countData,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_silent(ccNone<-clusterSingle(countData,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_silent(cm<-clusterMany(countData, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=TRUE))
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SE
expect_silent(ccVar<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE)
))
expect_silent(ccNone<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_message(cm<-clusterMany(testSE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"),verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=TRUE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SCE
expect_silent(ccVar<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=TRUE)
)
)
expect_silent(ccNone<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=TRUE))
expect_message(cm<-clusterMany(testSCE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"),verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=TRUE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#CE
expect_silent(ccVar2<-clusterSingle(ccVar,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccPCA2<-clusterSingle(ccPCA,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccNone2<-clusterSingle(ccNone,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3))))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(cm2<-clusterMany(cm, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3)
)
)
expect_equal(nClusterings(cm2),6)
expect_silent(params<-getClusterManyParams(cm2))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm2)[1,],2), expectTrans1)
})
test_that("`clusterMany` works with ClusterFunction objects",{
expect_silent(clustAll1<-clusterMany(sceSimDataDimRed,reduceMethod="PCA",
ks=c(3,4),clusterFunction=listBuiltInFunctions()[1:2],
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE,random.seed=1250))
expect_silent(clustAll2<-clusterMany(sceSimDataDimRed,reduceMethod="PCA",
ks=c(3,4),clusterFunction=getBuiltInFunction(listBuiltInFunctions()[1:2]),
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE,random.seed=1250))
expect_equal(clustAll2,clustAll1)
})
epurdom/clusterExperiment documentation built on April 28, 2024, 8:17 p.m.
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context("clusterMany")
test_that("`clusterMany` works with matrix, list of data, ClusterExperiment objects, and
SummarizedExperiments", {
#check all builtin methods
expect_silent(clustNothing <- clusterMany(mat,
ks=c(3,4),clusterFunction=listBuiltInFunctions(),
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE, makeMissingDiss=TRUE))
expect_silent(clustDF <- clusterMany(data.frame(mat),
ks=c(3,4),clusterFunction=listBuiltInFunctions(),
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE, makeMissingDiss=TRUE))
expect_is(clustNothing, "ClusterExperiment")
expect_is(clustNothing, "SingleCellExperiment")
expect_is(clustNothing, "SummarizedExperiment")
expect_silent(clustNothing2 <- clusterMany(se, ks=c(3,4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_equal(colData(clustNothing2),colData(se))
expect_equal(rownames(clustNothing2),rownames(se))
expect_equal(colnames(clustNothing2),colnames(se))
expect_equal(metadata(clustNothing2),metadata(se))
expect_equal(rowData(clustNothing2),rowData(se))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing))
expect_true(all(clusterTypes(clustNothing)=="clusterMany"))
#test running on ClusterExperiment Object -- should add the new clustering
expect_silent(clustNothing3 <- clusterMany(ccSE,
ks=c(3,4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE, verbose=FALSE))
expect_true(nClusterings(clustNothing3) == nClusterings(ccSE) + 2)
expect_equal(colData(clustNothing3),colData(ccSE))
expect_equal(rownames(clustNothing3),rownames(ccSE))
expect_equal(colnames(clustNothing3),colnames(ccSE))
expect_equal(metadata(clustNothing3),metadata(ccSE))
expect_equal(rowData(clustNothing3),rowData(ccSE))
expect_silent(test <- clusterSingle(se, subsample=FALSE,
sequential=FALSE,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=4)),
isCount=FALSE))
expect_silent(clustNothing3<- clusterMany(test,
ks=c(3,4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE, verbose=FALSE))
expect_silent(clustNothing4<- clusterMany(clustNothing3,
ks=c(3:4),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, eraseOld=TRUE))
expect_equal(clustNothing3,clustNothing4)
expect_silent(clustNothing5<- clusterMany(clustNothing3,
ks=c(5:6),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, eraseOld=FALSE))
expect_equal(NCOL(clusterMatrix(clustNothing5)),5)
expect_silent(ppIndex<-workflowClusterDetails(clustNothing5))
expect_equal(as.numeric(table(ppIndex[,"iteration"])),c(2,2))
})
test_that("`clusterMany` works with SingleCellExperiment", {
#check with sce that has dimRed:
#takes a while with all functions, but sometimes turn up surprises.
#for some reason if do clusterFunction=listBuiltInFunctions(),
# expect_silent gets warning, but not if run myself.
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction=listBuiltInFunctions()[[kk]],
makeMissingDiss=TRUE,
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE))
}
expect_equal(colData(clustNothing2),colData(sceSimDataDimRed))
expect_equal(rownames(clustNothing2),rownames(sceSimDataDimRed))
expect_equal(colnames(clustNothing2),colnames(sceSimDataDimRed))
expect_equal(metadata(clustNothing2),metadata(sceSimDataDimRed))
expect_equal(rowData(clustNothing2),rowData(sceSimDataDimRed))
expect_equal(reducedDims(clustNothing2),reducedDims(sceSimDataDimRed))
})
# # FIXME: need to make this operational
# test_that("`clusterMany` matches `clusterSingle` results", {
#
# subArgs<-list(clusterFunction="kmeans",classifyMethod="All")
# expect_message(ce<-clusterMany(smSimSE,
# isCount = FALSE,
# ks = 4:5,
# alphas=c(0.1),
# reduceMethod="PCA",
# nReducedDims=10,
# minSizes=1,
# subsample=TRUE,
# sequential=TRUE,
# clusterFunction="hierarchical01",
# subsampleArgs=subArgs,
# makeMissingDiss=TRUE, verbose=FALSE,
# random.seed=176201),"Not all of the methods requested in 'reduceMethod' have been calculated")
#
# mainArgs<-list( clusterFunction="hierarchical01",minSize=1,
# clusterArgs=list(alpha=0.1))
# seqArgs<-list(k0=4,beta=0.9)
# set.seed(176201)
# expect_silent(ce1<-clusterSingle(smSimSE,
# isCount = FALSE,
# saveSubsamplingMatrix=TRUE,
# reduceMethod="PCA",
# nDims=10,
# subsample=TRUE,
# sequential=TRUE,
# mainClusterArgs=mainArgs,
# subsampleArgs=subArgs,
# seqArgs=seqArgs,
# makeMissingDiss=TRUE
# ))
# expect_equal(primaryCluster(ce),primaryCluster(ce1))
#
# })
test_that("`clusterMany` works with reduceMethod a reducedDims",{
#check picking all dims in single reduceMethod same as apply directly to matrix
expect_silent(clustNothing <-
clusterMany(t(reducedDims(sceSimDataDimRed)[["PCA"]]),
ks=c(3,4),clusterFunction="pam",
reduceMethod="none",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam",
reduceMethod="PCA",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
expect_equal(NCOL(clusterMatrix(clustNothing)),2)
expect_equal(NCOL(clusterMatrix(clustNothing3)),2)
expect_equal(NCOL(clusterMatrix(clustNothing3)),2)
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
# check picking certain dims in single
# reduceMethod same as apply directly to matrix
# and that get right reducedDim returned
expect_silent(clustNothing <-
clusterMany(simData,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="PCA",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(NCOL(clusterMatrix(clustNothing)),4)
expect_equal(abs(reducedDim(clustNothing,"PCA")),
abs(reducedDim(sceSimDataDimRed,"PCA")[,1:6]))
expect_silent(clustNothing2 <-
clusterMany(sceSimDataDimRed,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="PCA",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(NCOL(clusterMatrix(clustNothing2)),4)
expect_equal(reducedDim(clustNothing2,"PCA"),
reducedDim(sceSimDataDimRed,"PCA"))
expect_message(clustNothing4 <-
clusterMany(sceSimData,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="PCA", clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(clusterMatrix(clustNothing2),
clusterMatrix(clustNothing4))
expect_message(clustNothingBoth1<-
clusterMany(clustNothing4,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod=c("PCA","mad"),
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, verbose=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated")
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages( clustNothingBoth2<-
clusterMany(clustNothingBoth1,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod=c("PCA","mad"),
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, verbose=FALSE)
)
)
expect_equal(clusterMatrix(clustNothingBoth1,
which="clusterMany"), clusterMatrix(clustNothingBoth2,
which="clusterMany"))
#check picking reduceMethod="none" same as apply directly to matrix
expect_silent(clustNothing <-
clusterMany(simData, ks=c(3,4),
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(sceSimDataDimRed, ks=c(3,4),
clusterFunction="pam", reduceMethod="none",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
#checks that nReducedDims ignored if reduceMethod="none"
expect_silent(clustNothing <-
clusterMany(simData,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="none",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,
verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(sceSimDataDimRed,
ks=c(3,4),nReducedDims=c(5:6),
reduceMethod="none",
clusterFunction="pam", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
})
test_that("`clusterMany` works with reduceMethod a filtering",{
expect_message(clustNothing4 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam", reduceMethod="mad",
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_error(clustNothing5 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam", reduceMethod=c("mad","cv"),
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE),"do not match any stored or built-in filtering statistics or dimensionality reduction")
expect_message(clustNothing5 <- clusterMany(sceSimDataDimRed,
ks=c(3,4),clusterFunction="pam", reduceMethod=c("mad","abscv"),
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_true(all(filterNames(sceSimDataDimRed) %in% filterNames(clustNothing5)))
expect_true(all(c("mad","abscv","var","mean") %in% filterNames(clustNothing5)))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(clusterMany(clustNothing5,
ks=c(3,4),clusterFunction="pam", reduceMethod=c("mad","abscv"),
subsample=FALSE, sequential=FALSE, verbose=FALSE)
)
)
})
test_that("`clusterMany` works with hdf5", {
# These are slow!
skip_on_os("windows")
skip_on_os("mac")
########
#Check if use PCA (not in hdf5) changes nothing, as expect.
########
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <- clusterMany(hdfSCE,
ks=c(3,4),clusterFunction=listBuiltInFunctions()[[kk]],
makeMissingDiss=TRUE,
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
}
expect_silent(clustNothing <-
clusterMany(t(reducedDims(sceSimDataDimRed)[["PCA"]]),
ks=c(3,4),clusterFunction="pam",
reduceMethod="none",
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
expect_silent(clustNothing3 <-
clusterMany(hdfSCE,
ks=c(3,4),clusterFunction="pam",
reduceMethod="PCA", subsample=FALSE,
sequential=FALSE, isCount=FALSE,verbose=FALSE))
expect_equal(clusterMatrix(clustNothing), clusterMatrix(clustNothing3))
expect_equal(NCOL(clusterMatrix(clustNothing)),2)
expect_equal(NCOL(clusterMatrix(clustNothing3)),2)
########
#Check if not using PCA (reduceMethod = "none")
########
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <-
clusterMany(hdfSCE,reduceMethod = "none",
ks=c(3,4), makeMissingDiss=TRUE,
clusterFunction=listBuiltInFunctions()[[kk]],
subsample=FALSE, sequential=FALSE,
isCount=FALSE,verbose=FALSE))
}
########
#Check directly on hdf5 object
########
for(kk in 1:length(listBuiltInFunctions())){
expect_silent(clustNothing2 <-
clusterMany(assay(hdfObj),reduceMethod = "none",
ks=c(3,4),clusterFunction=listBuiltInFunctions()[[kk]],
subsample=FALSE, sequential=FALSE,
makeMissingDiss=TRUE,
isCount=FALSE,verbose=FALSE))
}
})
test_that("`clusterMany` works changing parameters", {
# These are slow!
skip_on_os("windows")
skip_on_os("mac")
#--------
#check dim reduce in combination
#--------
expect_silent(cc <- clusterMany(mat,
ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var","abscv","mad"),
clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
verbose=FALSE, isCount=FALSE))
expect_equal(sort(reducedDimNames(cc)),sort(c("PCA")))
expect_equal(sort(filterNames(cc)),sort(c("var","abscv","mean","mad")))
expect_message(cc2 <- clusterMany(se,
ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var","abscv","mad"),
clusterFunction="pam",
subsample=FALSE, sequential=FALSE,
verbose=FALSE, isCount=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(sort(reducedDimNames(cc2)),sort(c("PCA")))
expect_equal(sort(filterNames(cc2)),
sort(c("b","var","abscv","mean","mad")))
expect_message(cc3 <- clusterMany(sce, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var","abscv","mad"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(sort(reducedDimNames(cc3)),sort(c("PCA")))
expect_equal(sort(filterNames(cc3)),sort(c("b","var","abscv","mean","mad")))
#Only existing values
expect_silent(cc4 <- clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none","Red1","Filter1","Filter2"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_equal(sort(reducedDimNames(cc4)),sort(c("Red1")))
expect_equal(sort(filterNames(cc4)),sort(c("b","Filter1","Filter2")))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages( ceReRun <- clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none","Red1","Filter1","Filter2"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE)
)
)
expect_equal(sort(reducedDimNames(ceReRun)),sort(reducedDimNames(cc4)))
expect_equal(sort(filterNames(ceReRun)),sort(filterNames(cc4)))
#Only existing values
expect_silent(cc4 <- clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none","Red1","Filter1","Filter2"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_equal(sort(reducedDimNames(cc4)),sort(c("Red1")))
expect_equal(sort(filterNames(cc4)),sort(c("b","Filter1","Filter2")))
#--------
# Mixing saved and unsaved (gives warnings/errors)
#--------
#following gives warning because can't mix saved and calculate internally
notAllWarning<-"All values of 'reduceMethod' need to either match an existing"
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),notAllWarning)
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),notAllWarning)
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),notAllWarning)
expect_error(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),
notAllWarning)
#repeat for ce
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),notAllWarning)
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),notAllWarning)
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),notAllWarning)
expect_error(clusterMany(cc4, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),
notAllWarning)
#--------
# Mixing mix across filter/reduceMethod okay
#--------
sceSimData2<-sceFull
reducedDims(sceSimData2)<-SimpleList()
expect_message(c1<-clusterMany(sceSimData2, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(clusterExperiment:::filterStats(c1),clusterExperiment:::filterStats(sceSimData2))
expect_equal(reducedDimNames(c1),"PCA")
sceSimData3<-sceFull
rowData(sceSimData3)<-NULL
expect_message(c2<-clusterMany(sceSimData3, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(reducedDims(c2),reducedDims(sceSimData3))
expect_equal(filterNames(c2),"var")
#repeat for ce
ce5<-cc4
reducedDims(ce5)<-SimpleList()
expect_message(c1<-clusterMany(ce5, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("PCA"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(clusterExperiment:::filterStats(c1),clusterExperiment:::filterStats(ce5))
expect_equal(reducedDimNames(c1),"PCA")
ce6<-cc4
rowData(ce6)<-NULL
expect_message(c2<-clusterMany(ce6, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE),"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(reducedDims(c2),reducedDims(ce6))
expect_equal(filterNames(c2),"var")
#--------
#check if only dim reduction
#--------
expect_silent(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
sceFull2<-makeReducedDims(sceFull,reducedDims="PCA",maxDims=10,isCount=FALSE)
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10),nReducedDims=c(2),
reduceMethod=c("PCA","Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10),nReducedDims=c(2),
reduceMethod=c("Red1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
#--------
#check only filter
#--------
expect_silent(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
sceFull2<-makeFilterStats(sceFull,filterStat="var",isCount=FALSE)
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var","Filter1"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
expect_silent(clusterMany(sceFull2, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
#--------
#check only none
#--------
expect_silent(clusterMany(sceFull, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(2),
reduceMethod=c("none"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,verbose=FALSE, isCount=FALSE))
#--------
#check returning paramMatrix
#--------
expect_silent(param <- clusterMany(mat,
ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),reduceMethod=c("none","PCA","var"),
clusterFunction="pam", subsample=FALSE, sequential=FALSE,run=FALSE,verbose=FALSE,
isCount=FALSE))
# #check that giving param$paramMatrix works -- not implemented...
# cc2 <- clusterMany(mat, ks=c(3,4),nFilterDims=c(10, 15),nReducedDims=c(3,4),
# reduceMethod=c("none","PCA","var"),clusterFunction="pam",
# subsample=FALSE, sequential=FALSE,verbose=FALSE,
# isCount=FALSE,paramMatrix=param$paramMatrix, mainClusterArgs=param$mainClusterArgs,
# seqArgs=param$seqArgs,subsampleArgs=param$subsampleArgs)
# expect_equal(cc,cc2)
expect_silent(cc2 <- clusterMany(mat, ks=c(3,4),clusterFunction="pam",
distFunction=c("euclidean","manhattan",NA),
subsample=FALSE, sequential=FALSE,verbose=FALSE,
isCount=FALSE, makeMissingDiss=TRUE))
# # #check giving distance -- this still doesn't work.
# # #problem to just give dist because need to grab from global environment
# # # So doesn't work in testthat
# dist1<-function(x){dist(x,method="manhattan")}
# dist2<-function(x){dist(x)}
# expect_silent(cc <- clusterMany(mat, ks=c(3,4),clusterFunction="pam",
# distFunction=c("dist1","dist2",NA),
# subsample=FALSE, sequential=FALSE,verbose=FALSE,
# isCount=FALSE))
# expect_equal(unname(clusterMatrix(cc)),unname(clusterMatrix(cc2)))
#
#check doesn't spit out warnings because alphas/mainClustering args not match
expect_silent(clusterMany(mat,
clusterFunction=c("pam","hierarchical01"),
ks=c(3,4),
alphas=c(0.1,0.2),
subsample=FALSE, sequential=FALSE,
verbose=FALSE, makeMissingDiss=TRUE,
mainClusterArgs=list(clusterArgs=list(evalClusterMethod="average")),
isCount=FALSE))
#check doesn't spit out warnings because alphas/mainClustering args not match
expect_silent(clusterMany(mat,
clusterFunction=c("pam","hierarchical01"),ks=c(3,4),
betas=c(.7,.9), minSizes=c(3,5),
subsample=FALSE, makeMissingDiss=TRUE, sequential=FALSE,verbose=FALSE,
mainClusterArgs=list(clusterArgs=list(evalClusterMethod="average")),
isCount=FALSE))
})
test_that("`getClusterManyParams` works", {
expect_silent(cc<-clusterMany(mat, ks=c(3,4),nFilterDims=c(10,15),nReducedDims=c(3,4),
reduceMethod=c("none","PCA","var"),clusterFunction="pam",
subsample=FALSE, sequential=FALSE,run=TRUE,verbose=FALSE,
isCount=FALSE))
expect_silent(cc<-makeConsensus(cc,proportion=1,whichClusters = "clusterMany"))
expect_silent(paramAll<-getClusterManyParams(cc))
expect_equal(sort(colnames(paramAll)),sort(c("clusteringIndex", "reduceMethod", "nReducedDims", "nFilterDims", "k")))
expect_true(is.data.frame(paramAll))
expect_equal(sort(as.character(unique(paramAll[,"reduceMethod"]))),sort(c("none","var","PCA")))
expect_equal(sort(unique(paramAll[,"nReducedDims"]),na.last=TRUE),sort(c(NA,3,4),na.last=TRUE))
expect_equal(sort(unique(paramAll[,"nFilterDims"]),na.last=TRUE),sort(c(NA,10,15),na.last=TRUE))
expect_true(is.numeric(paramAll[,"k"]))
# check simplify=TRUE
expect_silent(paramSub<-getClusterManyParams(cc,whichClusters=c(4,6),
simplify=TRUE))
expect_equal(sort(colnames(paramSub)),sort(c("clusteringIndex", "reduceMethod","nFilterDims")))
expect_true(is.data.frame(paramSub))
expect_equal(sort(unique(paramSub[,"nFilterDims"]),na.last=TRUE),c(10,NA))
expect_warning(getClusterManyParams(cc,whichClusters=1:5),"some clusters indicated in 'whichClusters' do not have type 'clusterMany'")
expect_warning(getClusterManyParams(cc,whichClusters=1),"did not return any clusters of type 'clusterMany'")
expect_warning(getClusterManyParams(cc,whichClusters="mergeClusters"),"did not return any clusters")
})
test_that("`clusterMany` consistent results (no transformation)", {
#----
#check get the same result from previous times when transform the data
#Relies on having these checks in clusterSingle, so know clusterSingle is right
#----
#make it big enough can do pca and filter...
contData<-simData[,1:20]
expectTrans1<-round(contData[1,],2)
expect_silent(testSE<-SummarizedExperiment(contData))
expect_silent(testSCE<-as(testSE,"SingleCellExperiment"))
#matrix
expect_silent(ccVar<-clusterSingle(contData,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_silent(ccPCA<-clusterSingle(contData,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_silent(ccNone<-clusterSingle(contData,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_silent(cm<-clusterMany(contData, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=FALSE))
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SE
expect_silent(ccVar<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE)
)
)
expect_silent(ccNone<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_message(cm<-clusterMany(testSE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE, verbose=FALSE,
reduceMethod=c("PCA","var","none"),
nReducedDims=3, nFilterDims=3,isCount=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SCE
expect_silent(ccVar<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE)
)
)
expect_silent(ccNone<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=FALSE))
expect_message(cm<-clusterMany(testSCE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"),verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=FALSE),
"Not all of the methods requested in 'reduceMethod' have been calculated.")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#CE
expect_silent(ccVar2<-clusterSingle(ccVar,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccPCA2<-clusterSingle(ccPCA,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccNone2<-clusterSingle(ccNone,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(cm2<-clusterMany(cm, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3)
)
)
expect_equal(nClusterings(cm2),6)
expect_silent(params<-getClusterManyParams(cm2))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm2)[1,],2), expectTrans1)
})
test_that("`clusterMany` consistent results (with transformation)", {
#----
#check get the same result from previous times when transform the data
#Relies on tests in clusterSingle being right
#----
#make it big enough can do pca and filter...
countData<-simCount[,1:20]
expect_silent(testSE<-SummarizedExperiment(countData))
expect_silent(testSCE<-as(testSE,"SingleCellExperiment"))
expectTrans1<-round(log2(countData[1,]+1),2)
#matrix
expect_silent(ccVar<-clusterSingle(countData,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_silent(ccPCA<-clusterSingle(countData,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_silent(ccNone<-clusterSingle(countData,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_silent(cm<-clusterMany(countData, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=TRUE))
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SE
expect_silent(ccVar<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE)
))
expect_silent(ccNone<-clusterSingle(testSE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
expect_message(cm<-clusterMany(testSE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"),verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=TRUE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#SCE
expect_silent(ccVar<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3)),
isCount=TRUE))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(ccPCA<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=TRUE)
)
)
expect_silent(ccNone<-clusterSingle(testSCE,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3)),
isCount=TRUE))
expect_message(cm<-clusterMany(testSCE, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"),verbose=FALSE,
nReducedDims=3, nFilterDims=3,isCount=TRUE),"Not all of the methods requested in 'reduceMethod' have been calculated")
expect_equal(nClusterings(cm),3)
expect_silent(params<-getClusterManyParams(cm))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm)[1,],2), expectTrans1)
#CE
expect_silent(ccVar2<-clusterSingle(ccVar,
subsample=FALSE, sequential=FALSE, reduceMethod="var",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccPCA2<-clusterSingle(ccPCA,
subsample=FALSE, sequential=FALSE, reduceMethod="PCA",
nDims=3, clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",clusterArgs=list(k=3))))
expect_silent(ccNone2<-clusterSingle(ccNone,
subsample=FALSE, sequential=FALSE, reduceMethod="none",
nDims=NA,clusterLabel="redo",
mainClusterArgs=list(clusterFunction="pam",
clusterArgs=list(k=3))))
## Issue with message created "Found more than one class "Annotated" in cache; using the first, from namespace 'S4Vectors'" message
## Now just checks no new warnings.
expect_silent(
suppressMessages(cm2<-clusterMany(cm, clusterFunction="pam",ks=3,
subsample=FALSE, sequential=FALSE,
reduceMethod=c("PCA","var","none"), verbose=FALSE,
nReducedDims=3, nFilterDims=3)
)
)
expect_equal(nClusterings(cm2),6)
expect_silent(params<-getClusterManyParams(cm2))
expect_equal(primaryCluster(ccPCA),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="PCA"]])
expect_equal(primaryCluster(ccVar),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="var"]])
expect_equal(primaryCluster(ccNone),clusterMatrix(cm2)[,params$clusteringIndex[params$reduceMethod=="none"]])
expect_equal(round(transformData(cm2)[1,],2), expectTrans1)
})
test_that("`clusterMany` works with ClusterFunction objects",{
expect_silent(clustAll1<-clusterMany(sceSimDataDimRed,reduceMethod="PCA",
ks=c(3,4),clusterFunction=listBuiltInFunctions()[1:2],
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE,random.seed=1250))
expect_silent(clustAll2<-clusterMany(sceSimDataDimRed,reduceMethod="PCA",
ks=c(3,4),clusterFunction=getBuiltInFunction(listBuiltInFunctions()[1:2]),
subsample=FALSE, sequential=FALSE, isCount=FALSE,verbose=FALSE,random.seed=1250))
expect_equal(clustAll2,clustAll1)
})
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