Nothing
.TARGET_seqnames <- Rle(factor(c("chr1", "chr2")))
.TARGET_ranges <- IRanges(c(1, 10), c(5, 20))
.TARGET_strand <- Rle(strand("*"), 2)
.TARGET_gr <- GRanges(.TARGET_seqnames, .TARGET_ranges, .TARGET_strand)
.TARGET_ref <- c("T", "A")
.TARGET_alt <- c("C", "T")
.TARGET_refDepth <- as.integer(c(5, 10))
.TARGET_altDepth <- as.integer(c(7, 6))
.TARGET_totalDepth <- as.integer(c(12, 17))
.TARGET_sampleNames <- factor(letters[1:2])
.TARGET_hardFilters <- FilterRules(list(a = function(x) softFilterMatrix(x)[,1]))
.TARGET_softFilterMatrix <- FilterMatrix(matrix = cbind(a = c(TRUE, FALSE)),
filterRules = .TARGET_hardFilters)
.TARGET_tumorSpecific <- c(FALSE, TRUE)
integerRle <- function(...) as(Rle(...), "integerRle")
characterRle <- function(...) as(Rle(...), "characterRle")
factorRle <- function(...) as(Rle(...), "factorRle")
make_TARGET_VRanges_simple <- function() {
new("VRanges", .TARGET_gr, ref = .TARGET_ref,
alt = .TARGET_alt, totalDepth = integerRle(NA_integer_, 2),
refDepth = integerRle(NA_integer_, 2),
altDepth = integerRle(NA_integer_, 2),
sampleNames = factorRle(NA_character_, 2),
softFilterMatrix =
FilterMatrix(matrix(nrow = length(.TARGET_gr), ncol = 0L),
filterRules = FilterRules()),
hardFilters = FilterRules())
}
make_TARGET_VRanges <- function(i = seq_len(length(.TARGET_seqnames))) {
new("VRanges",
GRanges(.TARGET_seqnames, .TARGET_ranges, .TARGET_strand,
tumorSpecific = .TARGET_tumorSpecific)[i],
ref = .TARGET_ref[i],
alt = .TARGET_alt[i], totalDepth = .TARGET_totalDepth[i],
refDepth = .TARGET_refDepth[i], altDepth = .TARGET_altDepth[i],
sampleNames = .TARGET_sampleNames[i],
softFilterMatrix = .TARGET_softFilterMatrix[i,,drop=FALSE],
hardFilters = .TARGET_hardFilters)
}
make_TARGET_VRanges_empty <- function() {
new("VRanges", GRanges(), ref = character(),
alt = characterRle(character()), totalDepth = integerRle(integer()),
refDepth = integerRle(integer()),
altDepth = integerRle(integer()),
sampleNames = factorRle(factor()),
softFilterMatrix = FilterMatrix(matrix(nrow = 0L, ncol = 0L),
filterRules = FilterRules()),
hardFilters = FilterRules())
}
test_VRanges_constructor <- function() {
vr <- make_TARGET_VRanges_simple()
## CHECK: 'ref' NA
ranges <- IRanges(c(1, 5), c(10, 20))
checkException(VRanges(.TARGET_seqnames, .TARGET_ranges, NA_character_))
## CHECK: depth < 0
checkException(VRanges(.TARGET_seqnames, .TARGET_ranges, .TARGET_ref,
refDepth = -1))
checkException(VRanges(.TARGET_seqnames, .TARGET_ranges, .TARGET_ref,
altDepth = -1))
## CHECK: invalid totalDepth sum
options(warn=2)
checkException(VRanges(.TARGET_seqnames, .TARGET_ranges,
.TARGET_ref, .TARGET_alt, 0, 1))
options(warn=0)
## CHECK: DNAStringSet handling (ref and alt); also, coercion depth=>integer
test.vr <- VRanges(.TARGET_seqnames, .TARGET_ranges,
DNAStringSet(.TARGET_ref), DNAStringSet(.TARGET_alt),
totalDepth = .TARGET_totalDepth)
vr@totalDepth <- .TARGET_totalDepth
checkIdentical(test.vr, vr)
## CHECK: recycling (every column)
test.vr <- VRanges(.TARGET_seqnames[1], .TARGET_ranges,
DNAStringSet(.TARGET_ref[1]), .TARGET_alt[1],
tumorSpecific = .TARGET_tumorSpecific,
totalDepth = .TARGET_totalDepth)
seqnames(vr) <- .TARGET_seqnames[1]
vr$tumorSpecific <- .TARGET_tumorSpecific
vr@ref <- rep(.TARGET_ref[1], 2)
alt(vr) <- .TARGET_alt[1]
checkIdentical(test.vr, vr)
## CHECK: coercion of 0/1 matrix to logical
test.vr <- VRanges(.TARGET_seqnames, .TARGET_ranges, .TARGET_ref, .TARGET_alt,
softFilterMatrix = cbind(a = c(1, 0)))
vr <- make_TARGET_VRanges_simple()
vr@softFilterMatrix <- as(.TARGET_softFilterMatrix, "matrix")
checkIdentical(test.vr, vr)
## CHECK: all arguments, with unnamed metadata
test.vr <- VRanges(.TARGET_seqnames, .TARGET_ranges, .TARGET_ref,
.TARGET_alt, .TARGET_totalDepth,
.TARGET_refDepth, .TARGET_altDepth,
tumorSpecific = .TARGET_tumorSpecific,
sampleNames = .TARGET_sampleNames,
softFilterMatrix = .TARGET_softFilterMatrix,
hardFilters = .TARGET_hardFilters)
vr <- make_TARGET_VRanges()
checkIdentical(test.vr, vr)
## CHECK: zero-length input
test.vr <- VRanges()
empty.vr <- make_TARGET_VRanges_empty()
checkIdentical(test.vr, empty.vr)
}
test_VRanges_extract <- function() {
vr <- make_TARGET_VRanges()
checkIdentical(vr[1], make_TARGET_VRanges(1))
checkIdentical(vr[0], make_TARGET_VRanges(0))
checkIdentical(vr[rep(1, 3)], make_TARGET_VRanges(rep(1, 3)))
checkIdentical(vr[c(2, 1)], make_TARGET_VRanges(c(2, 1)))
checkIdentical(vr[c(TRUE,FALSE)], make_TARGET_VRanges(c(TRUE,FALSE)))
checkIdentical(vr[TRUE], make_TARGET_VRanges(TRUE))
checkIdentical(vr[], make_TARGET_VRanges())
checkIdentical(vr[logical()], make_TARGET_VRanges(logical()))
vr$tumorSpecific <- NULL
checkIdentical(vr, make_TARGET_VRanges()[,integer()])
}
test_VRanges_accessors <- function() {
vr <- make_TARGET_VRanges()
checkIdentical(seqnames(vr), .TARGET_seqnames)
checkIdentical(ranges(vr), .TARGET_ranges)
checkIdentical(strand(vr), .TARGET_strand)
checkIdentical(ref(vr), .TARGET_ref)
checkIdentical(alt(vr), .TARGET_alt)
checkIdentical(refDepth(vr), .TARGET_refDepth)
checkIdentical(altDepth(vr), .TARGET_altDepth)
checkIdentical(totalDepth(vr), .TARGET_totalDepth)
checkIdentical(Biobase::sampleNames(vr), .TARGET_sampleNames)
checkIdentical(softFilterMatrix(vr), .TARGET_softFilterMatrix)
checkIdentical(hardFilters(vr), .TARGET_hardFilters)
checkIdentical(vr$tumorSpecific, .TARGET_tumorSpecific)
alt(vr) <- NA
checkIdentical(alt(vr), characterRle(NA, 2))
twoFilters <- rep(.TARGET_hardFilters, 2)
hardFilters(vr) <- twoFilters
checkIdentical(hardFilters(vr), twoFilters)
twoFilters <- .TARGET_softFilterMatrix[,c(1,1)]
softFilterMatrix(vr) <- twoFilters
checkIdentical(softFilterMatrix(vr), twoFilters)
}
test_VRanges_subassign <- function() {
vr <- make_TARGET_VRanges()
vr[2:1] <- vr
checkIdentical(vr, make_TARGET_VRanges(2:1))
vr <- make_TARGET_VRanges()
sampleNames(vr) <- Rle(sampleNames(vr))
vr2 <- vr
vr2[2:1] <- vr
checkIdentical(vr2, vr[2:1])
}
test_VRanges_combine <- function() {
vr <- make_TARGET_VRanges()
vr.rep <- vr[rep(seq_len(length(vr)), 2)]
vr.combined <- c(vr, vr)
checkIdentical(vr.combined, vr.rep)
}
test_VRanges_coerce <- function() {
df <- data.frame(as.data.frame(.TARGET_gr), ref = as.vector(.TARGET_ref),
alt = as.vector(.TARGET_alt),
totalDepth = as.vector(.TARGET_totalDepth),
refDepth = as.vector(.TARGET_refDepth),
altDepth = as.vector(.TARGET_altDepth),
sampleNames = as.factor(.TARGET_sampleNames),
softFilterMatrix = .TARGET_softFilterMatrix,
tumorSpecific = .TARGET_tumorSpecific,
stringsAsFactors = FALSE)
vr <- make_TARGET_VRanges()
checkIdentical(as.data.frame(vr), df)
}
make_TARGET_VRanges_vcf <- function() {
gr <- GRanges(c("1", "1", "3", "2", "1", "2"),
IRanges(c(1, 20, 15, 5, 20, 5), width = 1L), "*",
TS = c(TRUE, FALSE, FALSE, TRUE, TRUE, NA))
seqinfo(gr) <- Seqinfo(c("1", "3", "2"), c(NA, 22, 25),
genome = c(NA, "foo", NA))
new("VRanges", gr, ref = c("A", "C", "G", "T", "C", "T"),
alt = c("T", "G", NA, "A", "G", "C"),
totalDepth = c(NA, 10L, 15L, 10L, 5L, 3L),
refDepth = c(0L, 5L, 15L, 10L, NA, 2L),
altDepth = c(5L, NA, NA, 0L, 3L, 1L),
sampleNames = factorRle(factor(c("A", "B", "B", "A", "A", "B"))),
softFilterMatrix =
FilterMatrix(matrix = cbind(a = c(FALSE, TRUE, FALSE, TRUE, FALSE, TRUE),
b = c(FALSE, FALSE, TRUE, TRUE, NA, NA)),
filterRules = FilterRules(a = x > 1, b = c != "foo")),
hardFilters = FilterRules())
}
checkIdenticalVCF <- function(orig, vcf) {
vcf$QUAL <- NULL
if (!is.null(orig$TS))
orig$TS <- as.integer(orig$TS)
softFilterMatrix(orig) <- as(softFilterMatrix(orig), "matrix")
softFilterMatrix(vcf) <- as(softFilterMatrix(vcf), "matrix")
names(orig) <- names(vcf)
## Information loss due to binary nature of VCF filters
if (!identical(softFilterMatrix(orig), softFilterMatrix(vcf))) {
origFilt <- softFilterMatrix(orig)
origFilt[is.na(origFilt)] <- TRUE
origFilt[rowSums(origFilt) == 2 &
rowSums(softFilterMatrix(orig),na.rm=TRUE) != 2,] <- NA
softFilterMatrix(orig) <- origFilt
}
checkIdentical(orig, vcf)
}
test_VRanges_vcf <- function() {
dest <- tempfile()
vr <- make_TARGET_VRanges_vcf()
writeVcf(vr, dest)
vcf <- readVcf(dest, genome = "hg19")
perm <- c(1, 7, 8, 4, 2, 10)
vcf.vr <- as(vcf, "VRanges")[perm]
genome(vr) <- "hg19"
checkIdenticalVCF(vr, vcf.vr)
test.vcf <- asVCF(vr, info = "TS", filter = "a")
writeVcf(test.vcf, dest)
vcf <- readVcf(dest, genome = "hg19")
vcf.vr <- as(vcf, "VRanges")[perm]
## adjustments necessary, due to folding at INFO and FILTER
vcf.vr$TS[5:6] <- c(1L, NA)
softFilterMatrix(vcf.vr)[5,] <- cbind(FALSE, NA)
checkIdenticalVCF(vr, vcf.vr)
vrA <- vr[sampleNames(vr) == "A"]
runValue(sampleNames(vrA)) <- factor(runValue(sampleNames(vrA)))
vrA <- keepSeqlevels(vrA, unique(as.character(seqnames(vrA))))
writeVcf(vrA, dest)
vcfA <- readVcf(dest, genome = "hg19")
vcfA.vr <- as(vcfA, "VRanges")
checkIdenticalVCF(vrA, vcfA.vr)
geno(vcfA) <- SimpleList()
vrA.vcf <- as(vcfA, "VRanges")
vrA.stripped <- VRanges(seqnames(vrA), ranges(vrA), ref(vrA), alt(vrA),
sampleNames = sampleNames(vrA))
seqinfo(vrA.stripped) <- seqinfo(vrA)
checkIdenticalVCF(vrA.stripped, vrA.vcf)
vr <- VRanges(seqnames = c("chr1", "chr2"),
ranges = IRanges(c(1, 10), c(5, 20)),
ref = c("T", "A"), alt = c("C", "T"),
refDepth = c(5, 10), altDepth = c(7, 6),
totalDepth = c(12, 17), sampleNames = Rle(letters[1:2]),
softFilterMatrix =
cbind(depth = c(TRUE, FALSE)),
tumorSpecific = c(FALSE, TRUE))
vr_small <- vr
width(vr_small) <- 1
vcf_small <- as(vr_small, "VCF")
vr_back <- as(vcf_small, "VRanges")
vr_back$QUAL <- NULL
vr_back$tumorSpecific <- as.logical(vr_back$tumorSpecific)
checkIdentical(vr_small, vr_back[-(2:3)])
}
### GOT TIRED OF TESTING. I mean, seriously, that VCF stuff was insane.
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