tests/testthat/test-2mergeSEs.R
In microbiome/mia: Microbiome analysis
context("mergeSEs")
test_that("mergeSEs", {
# Load data
data(GlobalPatterns, package="mia")
data(esophagus, package="mia")
data(enterotype, package="mia")
tse1 <- GlobalPatterns[1:50, ]
tse2 <- esophagus[1:50, ]
tse3 <- enterotype[1:50, ]
# Expect errors
expect_error( mergeSEs(tse1) )
expect_error( mergeSEs(tse1, tse2, join = 1) )
expect_error( mergeSEs(tse1, tse2, join = TRUE) )
expect_error( mergeSEs(tse1, tse2, join = NA) )
expect_error( mergeSEs(tse1, tse2, collapse_samples = NA) )
expect_error( mergeSEs(tse1, tse2, collapse_samples = 1) )
expect_error( mergeSEs(tse1, tse2, collapse_samples = "test") )
expect_error( mergeSEs(tse1, tse2, collapse_samples = NULL) )
expect_error( mergeSEs(list(tse1, tse2, tse), join = "left") )
expect_error( mergeSEs(list(tse1, tse2, tse), join = "right") )
expect_error( mergeSEs(tse1, tse2, missing_values = TRUE ) )
expect_error( mergeSEs(tse1, tse2, missing_values = 36846 ) )
expect_error( mergeSEs(tse1, tse2, assay.type = "test") )
# Calculate relative transform to test assay.type
tse1 <- transformAssay(tse1, method = "relabundance")
expect_error( mergeSEs(tse1, tse2, assay.type = "relabundance") )
expect_error( mergeSEs(tse1, tse2, verbose = "test") )
expect_error( mergeSEs(tse1, tse2, verbose = 1) )
expect_error( mergeSEs(tse1, tse2, tse3) )
expect_error( mergeSEs(tse1) )
# Test that data match if there is only one element
#tse <- mergeSEs(list(tse1), assay.type = "relabundance")
tse <- mergeSEs(list(tse1), assay.type = "relabundance")
expect_equal( rowData(tse), rowData(tse1))
expect_equal( colData(tse), colData(tse1))
expect_equal( assay(tse, "relabundance"), assay(tse1, "relabundance"))
expect_equal( rowTree(tse), rowTree(tse1))
# Test that data match if there is only same elements
tse <- mergeSEs(list(tse1, tse1, tse1), assay.type = "relabundance")
# The order of taxa and samples changes
tse <- tse[ rownames(tse1), colnames(tse1) ]
expect_equal( rowData(tse), rowData(tse1))
expect_equal( as.data.frame( colData(tse) ), as.data.frame( colData(tse1)) )
# Disable attribute testing, since they might differ (e.g., vegan adds
# calculation details to attributes)
expect_equal( assay(tse, "relabundance"), assay(tse1, "relabundance"),
check.attributes = FALSE)
expect_equal( rowTree(tse), rowTree(tse1))
# Expect that rowTree is preserved if rownames match
tse <- mergeSEs(list(tse1, GlobalPatterns),
assay.type = "counts",
missing_values = NA)
expect_equal(rowTree(GlobalPatterns), rowTree(tse))
# Expect some NAs
tse <- mergeSEs(list(tse1, tse2), assay.type = "counts")
expect_true( any(is.na(assay(tse))) )
# Test that dimensions match
tse <- mergeSEs(tse1, tse2, missing_values = 0)
expect_equal( dim(tse), dim(tse1)+dim(tse2) )
# Expect no NAs in assay
expect_true( all(!is.na(assay(tse))) )
# Check that rows are merged correctly when all the rowData is used to
# specify rows
test <- mergeSEs(tse1, tse2, missing_values = 0, only.taxonomy = FALSE)
expect_equal(tse, test)
# Test that dimensions match
tse <- suppressWarnings(
mergeSEs(list(tse1, tse2, tse3), missing_values = "MISSING")
)
expect_equal( dim(tse), dim(tse1)+dim(tse2)+dim(tse3) )
# Expect some "MISSING"s
expect_true( any( assay(tse) == "MISSING" ) )
# Test rownames
expect_true( all(rownames(tse1) %in% rownames(tse)) )
expect_true( all(rownames(tse2) %in% rownames(tse)) )
expect_true( all(rownames(tse2) %in% rownames(tse)) )
# Test colnames
expect_true( all(colnames(tse1) %in% colnames(tse)) )
expect_true( all(colnames(tse2) %in% colnames(tse)) )
expect_true( all(colnames(tse3) %in% colnames(tse)) )
# CHECK FULL JOIN ###################################################
tse <- suppressWarnings(
mergeSEs(list(tse2, tse3, tse1, tse1[1:2, ], tse1[1, ]),
missing_values = NA)
)
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
assay2 <- as.matrix( assay(tse2, "counts") )
assay3 <- as.matrix( assay(tse3, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay1)
rownames <- rownames(assay1)
expect_equal( assay[rownames, colnames], assay1 )
colnames <- colnames(assay2)
rownames <- rownames(assay2)
expect_equal( assay[rownames, colnames], assay2 )
colnames <- colnames(assay3)
rownames <- rownames(assay3)
expect_equal( assay[rownames, colnames], assay3 )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
row_data2 <- as.data.frame(rowData(tse2) )
row_data3 <- as.data.frame( rowData(tse3) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data1)
rownames <- rownames(row_data1)
expect_equal( row_data[rownames, colnames], row_data1 )
colnames <- colnames(row_data2)
rownames <- rownames(row_data2)
expect_equal( row_data[rownames, colnames], row_data2 )
colnames <- colnames(row_data3)
rownames <- rownames(row_data3)
expect_equal( row_data[rownames, colnames, drop = FALSE], row_data3 )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
col_data2 <- as.data.frame( colData(tse2) )
col_data3 <- as.data.frame( colData(tse3) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data1)
rownames <- rownames(col_data1)
expect_equal( col_data[rownames, colnames], col_data1 )
colnames <- colnames(col_data2)
rownames <- rownames(col_data2)
expect_equal( col_data[rownames, colnames], col_data2 )
colnames <- colnames(col_data3)
rownames <- rownames(col_data3)
expect_equal( col_data[rownames, colnames], col_data3 )
# CHECK INNER JOIN ##############################################
tse <- suppressWarnings(
mergeSEs(list(tse1[, 1:5], tse1[, 5:10], tse3[1:20, 6:10]),
join = "inner")
)
expect_true( nrow(tse) == 0 )
expect_equal( rowTree(tse), NULL )
tse <- mergeSEs(list(tse1[, 1:5], tse1[, 5:10], tse1[1:20, 6:10]),
join = "inner", collapse_samples = TRUE)
expect_true( all(dim(tse) == c(20, 10)) )
expect_equal( rowTree(tse), rowTree(tse1) )
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay)
rownames <- rownames(assay)
expect_equal( assay1[rownames, colnames], assay )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data)
rownames <- rownames(row_data)
expect_equal( row_data1[rownames, colnames], row_data )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data)
rownames <- rownames(col_data)
expect_equal( col_data1[rownames, colnames], col_data )
# CHECK LEFT JOIN ##############################################
tse <- mergeSEs(list(tse1[11:20, 1:13], tse1[10:50, 7:20]),
join = "left", collapse_samples = TRUE)
expect_true( all(dim(tse) == c(10, 20)) )
expect_equal( rowTree(tse), rowTree(tse1) )
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay)
rownames <- rownames(assay)
expect_equal( assay1[rownames, colnames], assay )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data)
rownames <- rownames(row_data)
expect_equal( row_data1[rownames, colnames], row_data )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data)
rownames <- rownames(col_data)
expect_equal( col_data1[rownames, colnames], col_data )
# CHECK RIGHT JOIN ##############################################
tse <- mergeSEs(list(tse1[10:50, 1:13], tse1[1:10, 7:20]),
join = "right", missing_values = NA,
collapse_samples = TRUE)
expect_true( all(dim(tse) == c(10, 20)) )
expect_equal( rowTree(tse), rowTree(tse1) )
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay)
rownames <- rownames(assay)
assay1 <- assay1[rownames, colnames]
# Add NAs to original
na <- is.na(assay)
assay1[na] <- NA
expect_equal( assay1, assay )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data)
rownames <- rownames(row_data)
expect_equal( row_data1[rownames, colnames], row_data )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data)
rownames <- rownames(col_data)
expect_equal( col_data1[rownames, colnames], col_data )
# Check metadata
metadata(tse1) <- list(abc = c("abc", 123))
metadata(tse3) <- list(test = 1)
metadata(tse) <- list( cd = colData(tse) )
tse4 <- suppressWarnings(
mergeSEs(list(tse, tse3, tse2, tse1),
join = "inner")
)
expect_equal( nrow(tse4), 0 )
expect_equal( metadata(tse4)[["abc"]], metadata(tse1)[["abc"]] )
expect_equal( metadata(tse4)[["test"]], metadata(tse3)[["test"]] )
expect_equal( metadata(tse4)[["cd"]], metadata(tse)[["cd"]] )
expect_true( all( names(metadata(tse4)) %in%
c(names(metadata(tse1)), names(metadata(tse3)),
names(metadata(tse))) ) )
expect_equal( length( names(metadata(tse4))), 3)
# Check correct class
se1 <- as(tse1, "SummarizedExperiment")
rownames(se1) <- rownames(tse1)
tse <- mergeSEs(list(se1, se1, se1),
join = "full")
expect_true(class(tse) == "SummarizedExperiment")
suppressWarnings(
tse <- mergeSEs(list(se1,
as(tse1, "SingleCellExperiment"),
as(tse1, "TreeSummarizedExperiment")),
join = "inner")
)
expect_true(class(tse) == "SummarizedExperiment")
suppressWarnings(
tse <- mergeSEs(list(se1,
as(tse1, "SingleCellExperiment"),
as(tse1, "SingleCellExperiment")),
join = "full")
)
expect_true(class(tse) == "SummarizedExperiment")
suppressWarnings(
tse <- mergeSEs(x = as(tse1, "TreeSummarizedExperiment"),
y = as(tse1, "SingleCellExperiment"),
join = "right")
)
expect_warning(mergeSEs(x = as(tse1, "TreeSummarizedExperiment"),
y = as(tse1, "SingleCellExperiment"),
join = "right"))
expect_true(class(tse) == "SingleCellExperiment")
tse <- mergeSEs(list(as(tse1, "TreeSummarizedExperiment")),
join = "left")
expect_true(class(tse) == "TreeSummarizedExperiment")
# Test collapse_samples
tse_test <- mergeSEs(x = tse[1:28, 1:3],
y = tse[23, 1:5],
join = "full")
expect_equal( dim(tse_test), c(28, 8))
tse_test <- mergeSEs(x = list(tse[1:28, 1:3], tse[23, 1:5], tse[1, 1:10]),
join = "full")
expect_equal( dim(tse_test), c(28, 18))
expect_true( (all( c( paste0(rep(colnames(tse[, 1:3]), each=3), c("", ".2", ".3")),
paste0(rep(colnames(tse[, 4:5]), each=2), c("", ".3")),
colnames(tse[, 6:10]) ) %in%
colnames(tse_test) ) &&
all( colnames(tse_test) %in%
c( paste0(rep(colnames(tse[, 1:3]), each=3), c("", ".2", ".3")),
paste0(rep(colnames(tse[, 4:5]), each=2), c("", ".3")),
colnames(tse[, 6:10]) ) ) )
)
# Test that tree is added after agglomeration
agg_tse1 <- suppressWarnings( aggTSE(tse1, rowLevel = c(6,4,2)) )
tse <- mergeSEs(tse1, agg_tse1)
expect_equal(rowTree(tse), rowTree(tse1))
# Check that rownames match with node labels (These datasets have node labs
# that are named by rownames.)
tse <- mergeSEs(GlobalPatterns, esophagus)
expect_equal( rownames(tse), rowLinks(tse)$nodeLab )
# Check that rowData includes all the information
data(esophagus, package="mia")
data(GlobalPatterns, package="mia")
# Add arbitrary groups
rowData(esophagus)$group <- c(rep(c("A", "B", "C"), each = nrow(esophagus)/3),
rep("A", nrow(esophagus)-round(nrow(esophagus)/3)*3) )
rowData(esophagus)$group2 <- c(rep(c("A", "B", "C"), each = nrow(esophagus)/3),
rep("A", nrow(esophagus)-round(nrow(esophagus)/3)*3) )
rowData(GlobalPatterns)$group <- c(rep(c("C", "D", "E"), each = nrow(GlobalPatterns)/3),
rep("C", nrow(GlobalPatterns)-round(nrow(GlobalPatterns)/3)*3) )
tse <- mergeSEs(esophagus, GlobalPatterns)
rd_esophagus <- rowData(tse)[rownames(esophagus), ]
rd_gb <- rowData(tse)[rownames(GlobalPatterns), ]
expect_equal(rowData(esophagus), rd_esophagus[, colnames(rowData(esophagus))])
expect_equal(rowData(GlobalPatterns), rd_gb[, colnames(rowData(GlobalPatterns))])
# Check that variables with different class are not combined
tse1 <- esophagus
tse2 <- GlobalPatterns
tse3 <- GlobalPatterns[1:50, 1:10]
# Create variables with different class
colData(tse1)$group <- sample(c(1, 2, 3), ncol(tse1), replace = TRUE)
colData(tse2)$group <- sample(c("Group1", "Group2", "Group3"), ncol(tse2),
replace = TRUE)
colData(tse3)$group <- as.factor(sample(c("Group1", "Group2", "Group3"),
ncol(tse3), replace = TRUE))
tse <- expect_warning(mergeSEs(list(tse1, tse2, tse3)))
expect_true(ncol(colData(tse)) == length(unique(c( colnames(colData(tse1)),
colnames(colData(tse2)),
colnames(colData(tse3)))
))+2)
# Check that multiple assays are supported
tse1 <- transformAssay(tse1, method="relabundance")
tse2 <- transformAssay(tse2, method="relabundance")
tse3 <- transformAssay(tse3, method="relabundance")
tse_temp <- expect_warning( mergeSEs(list(tse1, tse2, tse3),
assay.type = c("counts",
"relabundance"),
join = "inner"))
expect_equal(assayNames(tse_temp), c("counts", "relabundance"))
tse_temp <- expect_warning(mergeSEs(list(tse1, tse2),
assay.type = c("counts", "relabundance", "test"),
join = "left"))
expect_equal(assayNames(tse_temp), c("counts", "relabundance"))
# Test that reference sequences stay the same
# Load data from miaTime package
skip_if_not(require("miaTime", quietly = TRUE))
data(SilvermanAGutData)
tse <- SilvermanAGutData
tse1 <- tse
rownames(tse1) <- paste0("Taxon", 1:nrow(tse))
# Merge
tse2 <- mergeSEs(tse1, tse)
# Test refseqs
ref1 <- referenceSeq(tse)
ref2 <- referenceSeq(tse2)[rownames(tse), ]
expect_equal(ref1, ref2)
})
microbiome/mia documentation built on May 17, 2024, 2:18 a.m.
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context("mergeSEs")
test_that("mergeSEs", {
# Load data
data(GlobalPatterns, package="mia")
data(esophagus, package="mia")
data(enterotype, package="mia")
tse1 <- GlobalPatterns[1:50, ]
tse2 <- esophagus[1:50, ]
tse3 <- enterotype[1:50, ]
# Expect errors
expect_error( mergeSEs(tse1) )
expect_error( mergeSEs(tse1, tse2, join = 1) )
expect_error( mergeSEs(tse1, tse2, join = TRUE) )
expect_error( mergeSEs(tse1, tse2, join = NA) )
expect_error( mergeSEs(tse1, tse2, collapse_samples = NA) )
expect_error( mergeSEs(tse1, tse2, collapse_samples = 1) )
expect_error( mergeSEs(tse1, tse2, collapse_samples = "test") )
expect_error( mergeSEs(tse1, tse2, collapse_samples = NULL) )
expect_error( mergeSEs(list(tse1, tse2, tse), join = "left") )
expect_error( mergeSEs(list(tse1, tse2, tse), join = "right") )
expect_error( mergeSEs(tse1, tse2, missing_values = TRUE ) )
expect_error( mergeSEs(tse1, tse2, missing_values = 36846 ) )
expect_error( mergeSEs(tse1, tse2, assay.type = "test") )
# Calculate relative transform to test assay.type
tse1 <- transformAssay(tse1, method = "relabundance")
expect_error( mergeSEs(tse1, tse2, assay.type = "relabundance") )
expect_error( mergeSEs(tse1, tse2, verbose = "test") )
expect_error( mergeSEs(tse1, tse2, verbose = 1) )
expect_error( mergeSEs(tse1, tse2, tse3) )
expect_error( mergeSEs(tse1) )
# Test that data match if there is only one element
#tse <- mergeSEs(list(tse1), assay.type = "relabundance")
tse <- mergeSEs(list(tse1), assay.type = "relabundance")
expect_equal( rowData(tse), rowData(tse1))
expect_equal( colData(tse), colData(tse1))
expect_equal( assay(tse, "relabundance"), assay(tse1, "relabundance"))
expect_equal( rowTree(tse), rowTree(tse1))
# Test that data match if there is only same elements
tse <- mergeSEs(list(tse1, tse1, tse1), assay.type = "relabundance")
# The order of taxa and samples changes
tse <- tse[ rownames(tse1), colnames(tse1) ]
expect_equal( rowData(tse), rowData(tse1))
expect_equal( as.data.frame( colData(tse) ), as.data.frame( colData(tse1)) )
# Disable attribute testing, since they might differ (e.g., vegan adds
# calculation details to attributes)
expect_equal( assay(tse, "relabundance"), assay(tse1, "relabundance"),
check.attributes = FALSE)
expect_equal( rowTree(tse), rowTree(tse1))
# Expect that rowTree is preserved if rownames match
tse <- mergeSEs(list(tse1, GlobalPatterns),
assay.type = "counts",
missing_values = NA)
expect_equal(rowTree(GlobalPatterns), rowTree(tse))
# Expect some NAs
tse <- mergeSEs(list(tse1, tse2), assay.type = "counts")
expect_true( any(is.na(assay(tse))) )
# Test that dimensions match
tse <- mergeSEs(tse1, tse2, missing_values = 0)
expect_equal( dim(tse), dim(tse1)+dim(tse2) )
# Expect no NAs in assay
expect_true( all(!is.na(assay(tse))) )
# Check that rows are merged correctly when all the rowData is used to
# specify rows
test <- mergeSEs(tse1, tse2, missing_values = 0, only.taxonomy = FALSE)
expect_equal(tse, test)
# Test that dimensions match
tse <- suppressWarnings(
mergeSEs(list(tse1, tse2, tse3), missing_values = "MISSING")
)
expect_equal( dim(tse), dim(tse1)+dim(tse2)+dim(tse3) )
# Expect some "MISSING"s
expect_true( any( assay(tse) == "MISSING" ) )
# Test rownames
expect_true( all(rownames(tse1) %in% rownames(tse)) )
expect_true( all(rownames(tse2) %in% rownames(tse)) )
expect_true( all(rownames(tse2) %in% rownames(tse)) )
# Test colnames
expect_true( all(colnames(tse1) %in% colnames(tse)) )
expect_true( all(colnames(tse2) %in% colnames(tse)) )
expect_true( all(colnames(tse3) %in% colnames(tse)) )
# CHECK FULL JOIN ###################################################
tse <- suppressWarnings(
mergeSEs(list(tse2, tse3, tse1, tse1[1:2, ], tse1[1, ]),
missing_values = NA)
)
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
assay2 <- as.matrix( assay(tse2, "counts") )
assay3 <- as.matrix( assay(tse3, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay1)
rownames <- rownames(assay1)
expect_equal( assay[rownames, colnames], assay1 )
colnames <- colnames(assay2)
rownames <- rownames(assay2)
expect_equal( assay[rownames, colnames], assay2 )
colnames <- colnames(assay3)
rownames <- rownames(assay3)
expect_equal( assay[rownames, colnames], assay3 )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
row_data2 <- as.data.frame(rowData(tse2) )
row_data3 <- as.data.frame( rowData(tse3) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data1)
rownames <- rownames(row_data1)
expect_equal( row_data[rownames, colnames], row_data1 )
colnames <- colnames(row_data2)
rownames <- rownames(row_data2)
expect_equal( row_data[rownames, colnames], row_data2 )
colnames <- colnames(row_data3)
rownames <- rownames(row_data3)
expect_equal( row_data[rownames, colnames, drop = FALSE], row_data3 )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
col_data2 <- as.data.frame( colData(tse2) )
col_data3 <- as.data.frame( colData(tse3) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data1)
rownames <- rownames(col_data1)
expect_equal( col_data[rownames, colnames], col_data1 )
colnames <- colnames(col_data2)
rownames <- rownames(col_data2)
expect_equal( col_data[rownames, colnames], col_data2 )
colnames <- colnames(col_data3)
rownames <- rownames(col_data3)
expect_equal( col_data[rownames, colnames], col_data3 )
# CHECK INNER JOIN ##############################################
tse <- suppressWarnings(
mergeSEs(list(tse1[, 1:5], tse1[, 5:10], tse3[1:20, 6:10]),
join = "inner")
)
expect_true( nrow(tse) == 0 )
expect_equal( rowTree(tse), NULL )
tse <- mergeSEs(list(tse1[, 1:5], tse1[, 5:10], tse1[1:20, 6:10]),
join = "inner", collapse_samples = TRUE)
expect_true( all(dim(tse) == c(20, 10)) )
expect_equal( rowTree(tse), rowTree(tse1) )
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay)
rownames <- rownames(assay)
expect_equal( assay1[rownames, colnames], assay )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data)
rownames <- rownames(row_data)
expect_equal( row_data1[rownames, colnames], row_data )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data)
rownames <- rownames(col_data)
expect_equal( col_data1[rownames, colnames], col_data )
# CHECK LEFT JOIN ##############################################
tse <- mergeSEs(list(tse1[11:20, 1:13], tse1[10:50, 7:20]),
join = "left", collapse_samples = TRUE)
expect_true( all(dim(tse) == c(10, 20)) )
expect_equal( rowTree(tse), rowTree(tse1) )
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay)
rownames <- rownames(assay)
expect_equal( assay1[rownames, colnames], assay )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data)
rownames <- rownames(row_data)
expect_equal( row_data1[rownames, colnames], row_data )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data)
rownames <- rownames(col_data)
expect_equal( col_data1[rownames, colnames], col_data )
# CHECK RIGHT JOIN ##############################################
tse <- mergeSEs(list(tse1[10:50, 1:13], tse1[1:10, 7:20]),
join = "right", missing_values = NA,
collapse_samples = TRUE)
expect_true( all(dim(tse) == c(10, 20)) )
expect_equal( rowTree(tse), rowTree(tse1) )
# Get assay (as.matrix to remove links)
assay <- as.matrix( assay(tse, "counts") )
assay1 <- as.matrix( assay(tse1, "counts") )
# Expect that the data can be found without modifications
colnames <- colnames(assay)
rownames <- rownames(assay)
assay1 <- assay1[rownames, colnames]
# Add NAs to original
na <- is.na(assay)
assay1[na] <- NA
expect_equal( assay1, assay )
# Get rowData (as.data.frame to remove links)
row_data <- as.data.frame( rowData(tse) )
row_data1 <- as.data.frame(rowData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(row_data)
rownames <- rownames(row_data)
expect_equal( row_data1[rownames, colnames], row_data )
# Get colData (as.data.frame to remove links)
col_data <- as.data.frame( colData(tse) )
col_data1 <- as.data.frame( colData(tse1) )
# Expect that the data can be found without modifications
colnames <- colnames(col_data)
rownames <- rownames(col_data)
expect_equal( col_data1[rownames, colnames], col_data )
# Check metadata
metadata(tse1) <- list(abc = c("abc", 123))
metadata(tse3) <- list(test = 1)
metadata(tse) <- list( cd = colData(tse) )
tse4 <- suppressWarnings(
mergeSEs(list(tse, tse3, tse2, tse1),
join = "inner")
)
expect_equal( nrow(tse4), 0 )
expect_equal( metadata(tse4)[["abc"]], metadata(tse1)[["abc"]] )
expect_equal( metadata(tse4)[["test"]], metadata(tse3)[["test"]] )
expect_equal( metadata(tse4)[["cd"]], metadata(tse)[["cd"]] )
expect_true( all( names(metadata(tse4)) %in%
c(names(metadata(tse1)), names(metadata(tse3)),
names(metadata(tse))) ) )
expect_equal( length( names(metadata(tse4))), 3)
# Check correct class
se1 <- as(tse1, "SummarizedExperiment")
rownames(se1) <- rownames(tse1)
tse <- mergeSEs(list(se1, se1, se1),
join = "full")
expect_true(class(tse) == "SummarizedExperiment")
suppressWarnings(
tse <- mergeSEs(list(se1,
as(tse1, "SingleCellExperiment"),
as(tse1, "TreeSummarizedExperiment")),
join = "inner")
)
expect_true(class(tse) == "SummarizedExperiment")
suppressWarnings(
tse <- mergeSEs(list(se1,
as(tse1, "SingleCellExperiment"),
as(tse1, "SingleCellExperiment")),
join = "full")
)
expect_true(class(tse) == "SummarizedExperiment")
suppressWarnings(
tse <- mergeSEs(x = as(tse1, "TreeSummarizedExperiment"),
y = as(tse1, "SingleCellExperiment"),
join = "right")
)
expect_warning(mergeSEs(x = as(tse1, "TreeSummarizedExperiment"),
y = as(tse1, "SingleCellExperiment"),
join = "right"))
expect_true(class(tse) == "SingleCellExperiment")
tse <- mergeSEs(list(as(tse1, "TreeSummarizedExperiment")),
join = "left")
expect_true(class(tse) == "TreeSummarizedExperiment")
# Test collapse_samples
tse_test <- mergeSEs(x = tse[1:28, 1:3],
y = tse[23, 1:5],
join = "full")
expect_equal( dim(tse_test), c(28, 8))
tse_test <- mergeSEs(x = list(tse[1:28, 1:3], tse[23, 1:5], tse[1, 1:10]),
join = "full")
expect_equal( dim(tse_test), c(28, 18))
expect_true( (all( c( paste0(rep(colnames(tse[, 1:3]), each=3), c("", ".2", ".3")),
paste0(rep(colnames(tse[, 4:5]), each=2), c("", ".3")),
colnames(tse[, 6:10]) ) %in%
colnames(tse_test) ) &&
all( colnames(tse_test) %in%
c( paste0(rep(colnames(tse[, 1:3]), each=3), c("", ".2", ".3")),
paste0(rep(colnames(tse[, 4:5]), each=2), c("", ".3")),
colnames(tse[, 6:10]) ) ) )
)
# Test that tree is added after agglomeration
agg_tse1 <- suppressWarnings( aggTSE(tse1, rowLevel = c(6,4,2)) )
tse <- mergeSEs(tse1, agg_tse1)
expect_equal(rowTree(tse), rowTree(tse1))
# Check that rownames match with node labels (These datasets have node labs
# that are named by rownames.)
tse <- mergeSEs(GlobalPatterns, esophagus)
expect_equal( rownames(tse), rowLinks(tse)$nodeLab )
# Check that rowData includes all the information
data(esophagus, package="mia")
data(GlobalPatterns, package="mia")
# Add arbitrary groups
rowData(esophagus)$group <- c(rep(c("A", "B", "C"), each = nrow(esophagus)/3),
rep("A", nrow(esophagus)-round(nrow(esophagus)/3)*3) )
rowData(esophagus)$group2 <- c(rep(c("A", "B", "C"), each = nrow(esophagus)/3),
rep("A", nrow(esophagus)-round(nrow(esophagus)/3)*3) )
rowData(GlobalPatterns)$group <- c(rep(c("C", "D", "E"), each = nrow(GlobalPatterns)/3),
rep("C", nrow(GlobalPatterns)-round(nrow(GlobalPatterns)/3)*3) )
tse <- mergeSEs(esophagus, GlobalPatterns)
rd_esophagus <- rowData(tse)[rownames(esophagus), ]
rd_gb <- rowData(tse)[rownames(GlobalPatterns), ]
expect_equal(rowData(esophagus), rd_esophagus[, colnames(rowData(esophagus))])
expect_equal(rowData(GlobalPatterns), rd_gb[, colnames(rowData(GlobalPatterns))])
# Check that variables with different class are not combined
tse1 <- esophagus
tse2 <- GlobalPatterns
tse3 <- GlobalPatterns[1:50, 1:10]
# Create variables with different class
colData(tse1)$group <- sample(c(1, 2, 3), ncol(tse1), replace = TRUE)
colData(tse2)$group <- sample(c("Group1", "Group2", "Group3"), ncol(tse2),
replace = TRUE)
colData(tse3)$group <- as.factor(sample(c("Group1", "Group2", "Group3"),
ncol(tse3), replace = TRUE))
tse <- expect_warning(mergeSEs(list(tse1, tse2, tse3)))
expect_true(ncol(colData(tse)) == length(unique(c( colnames(colData(tse1)),
colnames(colData(tse2)),
colnames(colData(tse3)))
))+2)
# Check that multiple assays are supported
tse1 <- transformAssay(tse1, method="relabundance")
tse2 <- transformAssay(tse2, method="relabundance")
tse3 <- transformAssay(tse3, method="relabundance")
tse_temp <- expect_warning( mergeSEs(list(tse1, tse2, tse3),
assay.type = c("counts",
"relabundance"),
join = "inner"))
expect_equal(assayNames(tse_temp), c("counts", "relabundance"))
tse_temp <- expect_warning(mergeSEs(list(tse1, tse2),
assay.type = c("counts", "relabundance", "test"),
join = "left"))
expect_equal(assayNames(tse_temp), c("counts", "relabundance"))
# Test that reference sequences stay the same
# Load data from miaTime package
skip_if_not(require("miaTime", quietly = TRUE))
data(SilvermanAGutData)
tse <- SilvermanAGutData
tse1 <- tse
rownames(tse1) <- paste0("Taxon", 1:nrow(tse))
# Merge
tse2 <- mergeSEs(tse1, tse)
# Test refseqs
ref1 <- referenceSeq(tse)
ref2 <- referenceSeq(tse2)[rownames(tse), ]
expect_equal(ref1, ref2)
})
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