test_that("do_findPeaks_MSW works", {
skip_on_os(os = "windows", arch = "i386")
first_file <- filterFile(fticr, file = 1)
spctr <- spectra(first_file)
expect_true(length(spctr) == 1)
mzs <- unname(mz(spctr[[1]]))
ints <- unname(intensity(spctr[[1]]))
feats1 <- do_findPeaks_MSW(mz = mzs[10000:20000],
int = ints[10000:20000],
snthresh = 100)
feats2 <- do_findPeaks_MSW(mz = mzs[10000:20000],
int = ints[10000:20000],
snthresh = 50)
expect_true(nrow(feats2) > nrow(feats1))
})
test_that("do_findChromPeaks_centWave works", {
skip_on_os(os = "windows", arch = "i386")
## We expect that changing a parameter has an influence on the result.
mzVals <- mz(xod_x)
intVals <- unlist(intensity(xod_x), use.names = FALSE)
## Define the values per spectrum:
valsPerSpect <- lengths(mzVals)
res1 <- do_findChromPeaks_centWave(mz = unlist(mzVals, use.names = FALSE),
int = intVals,
scantime = rtime(xod_x),
valsPerSpect,
snthresh = 100,
noise = 4000,
prefilter = c(3, 10000))
## Eventually disable the sleep option to improve speed!
res2 <- do_findChromPeaks_centWave(mz = unlist(mzVals, use.names = FALSE),
int = intVals,
scantime = rtime(xod_x),
valsPerSpect,
snthresh = 500,
noise = 4000, sleep = 0.00,
prefilter = c(3, 10000))
expect_true(nrow(res1) > nrow(res2))
})
test_that("beta calculation returns expected values", {
expect_lt(.get_beta_values(1:10, zero.rm = FALSE)["best_cor"], 0.0001)
expect_lt(.get_beta_values(1:10, zero.rm = FALSE)["beta_snr"], 2)
expect_lt(.get_beta_values(1:10)["best_cor"], 0.0001)
expect_lt(.get_beta_values(1:10)["beta_snr"], 2)
ideal_beta <- dbeta(seq(0, 1, length.out=10), 5, 5)
expect_gte(.get_beta_values(ideal_beta, zero.rm = FALSE)["best_cor"], 1)
expect_gte(.get_beta_values(ideal_beta, zero.rm = FALSE)["beta_snr"], 16)
expect_gte(.get_beta_values(ideal_beta)["best_cor"], 0.97)
expect_gte(.get_beta_values(ideal_beta)["beta_snr"], 1)
skew_beta <- dbeta(seq(0, 1, length.out=10), 3, 5)
expect_gte(.get_beta_values(ideal_beta, zero.rm = FALSE)["best_cor"], 1)
expect_gte(.get_beta_values(ideal_beta, zero.rm = FALSE)["beta_snr"], 16)
expect_gte(.get_beta_values(ideal_beta)["best_cor"], 0.97)
expect_gte(.get_beta_values(ideal_beta)["beta_snr"], 1)
rightskew_beta <- dbeta(seq(0, 1, length.out=10), 7, 5)
expect_gt(.get_beta_values(rightskew_beta, skews = c(3,5,7))["best_cor"], 0.95)
noise_beta <- dbeta(seq(0, 1, length.out=21), 5, 5)*10+runif(21)
expect_gt(.get_beta_values(noise_beta)["best_cor"], 0.9)
expect_no_error(.get_beta_values(runif(1)))
expect_no_error(.get_beta_values(runif(10)))
expect_no_error(.get_beta_values(runif(100)))
expect_length(.get_beta_values(1), 2)
expect_true(is.na(.get_beta_values(1)["best_cor"]))
expect_true(is.na(.get_beta_values(1)["beta_snr"]))
})
test_that("New beta columns perform as expected", {
# faahko_xod comes from testthat.R
# faahko_xod <- findChromPeaks(
# faahko_od, param = CentWaveParam(noise = 10000, snthresh = 40,
# prefilter = c(3, 10000)))
# Same params as before but with verboseBetaColumns = TRUE
beta_cwp <- CentWaveParam(noise = 10000, snthresh = 40,
prefilter = c(3, 10000),
verboseBetaColumns = TRUE)
faahko_xod_beta <- findChromPeaks(faahko_od, beta_cwp)
# Unit test - check that the new object contains expected columns
expect_contains(colnames(chromPeaks(faahko_xod_beta)),
c("beta_cor", "beta_snr"))
# Unit test - check that everything else in the object is the same
orig_chrompeaks <- chromPeaks(faahko_xod)
beta_chrompeaks <- chromPeaks(faahko_xod_beta)
expect_identical(orig_chrompeaks, beta_chrompeaks[,colnames(orig_chrompeaks)])
# Object will contain NAs because there are peaks <5 scans wide
expect_true(any(is.na(beta_chrompeaks[,"beta_snr"])))
beta_chrompeaks <- beta_chrompeaks[!is.na(beta_chrompeaks[,"beta_cor"]),]
# Unit test - check that beta values make sense
expect_true(all(beta_chrompeaks[,"beta_cor"]<=1))
expect_true(all(beta_chrompeaks[,"beta_cor"]>=-1))
expect_true(all(beta_chrompeaks[,"beta_snr"]>=0))
# Unit test - finds a single good peak (beta_cor>0.8, beta_snr>7)
# Skinny peak copied from below peaksWithCentWave tests
skinny_peak <- c(9107, 3326, 9523, 3245, 3429, 9394, 1123, 935, 5128, 8576,
2711, 3427, 7294, 8109, 9288, 6997, 9756, 8034, 1317, 8866, 13877,
14854, 28296, 57101, 92209, 151797, 222386, 299402, 365045, 394255,
402680, 363996, 293985, 222989, 147007, 94947, 52924, 32438,
11511, 10836, 8046, 601, 889, 5917, 2690, 5381, 9901, 8494, 3349,
8283, 3410, 5935, 3332, 7041, 3284, 7478, 76, 3739, 2158, 5507)
skinny_peak_rt <- seq_along(skinny_peak)+100
cw_output_beta <- .centWave_orig(int = skinny_peak, scantime = skinny_peak_rt,
mz=sort(rnorm(60)/1000+100),
valsPerSpect = rep(1, length(skinny_peak)),
peakwidth = c(20, 80), extendLengthMSW = TRUE,
verboseBetaColumns = TRUE, snthresh = 0)
expect_equal(nrow(cw_output_beta), 1)
# Known values to ensure performance doesn't degrade unexpectedly
expect_gt(cw_output_beta[,"beta_cor"], 0.8)
expect_gt(cw_output_beta[,"beta_snr"], 7)
# Unit test - finds a single noise peak (beta_cor < 0.5, beta_snr < 6)
# set.seed(123)
# noise_peak <- round(runif(100), 3)
noise_peak <- c(0.288, 0.788, 0.409, 0.883, 0.94, 0.046, 0.528, 0.892, 0.551,
0.457, 0.957, 0.453, 0.678, 0.573, 0.103, 0.9, 0.246, 0.042,
0.328, 0.955, 0.89, 0.693, 0.641, 0.994, 0.656, 0.709, 0.544,
0.594, 0.289, 0.147, 0.963, 0.902, 0.691, 0.795, 0.025, 0.478,
0.758, 0.216, 0.318, 0.232, 0.143, 0.415, 0.414, 0.369, 0.152,
0.139, 0.233, 0.466, 0.266, 0.858, 0.046, 0.442, 0.799, 0.122,
0.561, 0.207, 0.128, 0.753, 0.895, 0.374, 0.665, 0.095, 0.384,
0.274, 0.815, 0.449, 0.81, 0.812, 0.794, 0.44, 0.754, 0.629,
0.71, 0.001, 0.475, 0.22, 0.38, 0.613, 0.352, 0.111, 0.244,
0.668,
0.418, 0.788, 0.103, 0.435, 0.985, 0.893, 0.886, 0.175, 0.131,
0.653, 0.344, 0.657, 0.32, 0.188, 0.782, 0.094, 0.467, 0.512)
cw_output_beta <- .centWave_orig(int = noise_peak*100000,
scantime = seq_along(noise_peak),
mz=rep(530.1, length(noise_peak)),
valsPerSpect = rep(1, length(noise_peak)),
peakwidth = c(20, 80), extendLengthMSW = TRUE,
verboseBetaColumns = TRUE, snthresh = 0)
expect_equal(nrow(cw_output_beta), 1)
# Known values to ensure performance doesn't degrade unexpectedly
expect_lt(cw_output_beta[,"beta_cor"], 0.2)
expect_lt(cw_output_beta[,"beta_snr"], 6)
})
test_that("do_findChromPeaks_centWaveWithPredIsoROIs works", {
skip_on_os(os = "windows", arch = "i386")
tmp <- filterFile(od_x, 1)
mzVals <- mz(tmp)
intVals <- unlist(intensity(tmp), use.names = FALSE)
## initial centWave:
valsPerSpect <- lengths(mzVals)
feats_1 <- do_findChromPeaks_centWave(
mz = unlist(mzVals, use.names = FALSE), int = intVals,
prefilter = c(3, 5000),
scantime = rtime(tmp),
valsPerSpect = valsPerSpect, noise = 1500, verboseColumns = TRUE)
feats_2 <- do_findChromPeaks_addPredIsoROIs(
mz = unlist(mzVals, use.names = FALSE), int = intVals,
scantime = rtime(tmp), valsPerSpect = valsPerSpect, noise = 1500,
prefilter = c(3, 5000),
peaks. = feats_1)
expect_true(nrow(feats_1) < nrow(feats_2))
all_f <- do_findChromPeaks_centWaveWithPredIsoROIs(
mz = unlist(mzVals, use.names = FALSE), int = intVals,
scantime = rtime(tmp), prefilter = c(3, 5000),
valsPerSpect = valsPerSpect, noise = 1500)
expect_equal(all_f, feats_2)
})
test_that("do_findChromPeaks_massifquant works", {
skip_on_os(os = "windows", arch = "i386")
tmp <- filterFile(od_x, 1)
mz <- mz(tmp)
valsPerSpect <- lengths(mz)
mz <- unlist(mz, use.names = FALSE)
int <- unlist(intensity(tmp), use.names = FALSE)
rtime <- rtime(tmp)
res_2 <- do_findChromPeaks_massifquant(mz = mz, int = int,
valsPerSpect = valsPerSpect,
scantime = rtime)
expect_true(nrow(res_2) == 1542)
## With centWave:
res_3 <- do_findChromPeaks_massifquant(mz = mz, int = int,
valsPerSpect = valsPerSpect,
scantime = rtime, withWave = TRUE,
snthresh = 100, noise = 4000)
expect_true(nrow(res_3) < nrow(res_2))
})
test_that("do_findChromPeaks_matchedFilter works", {
skip_on_os(os = "windows", arch = "i386")
tmp <- filterFile(od_x, 1)
mzVals <- mz(tmp)
valsPerSpect <- lengths(mzVals)
mzVals <- unlist(mzVals, use.names = FALSE)
intVals <- unlist(intensity(tmp), use.names = FALSE)
res1 <- do_findChromPeaks_matchedFilter(mz = mzVals,
int = intVals,
scantime = rtime(tmp),
valsPerSpect,
binSize = 10)
res2 <- do_findChromPeaks_matchedFilter(mz = mzVals,
int = intVals,
scantime = rtime(tmp),
valsPerSpect,
binSize = 10,
snthresh = 100)
expect_true(nrow(res1) > nrow(res2))
res2 <- do_findChromPeaks_matchedFilter(mz = mzVals,
int = intVals,
scantime = rtime(tmp),
valsPerSpect,
binSize = 20)
expect_true(nrow(res1) > nrow(res2))
## with empty spectra - simulating issue #325
od_sub <- filterMz(od_x, mz = c(334.9, 344.1))
sps <- spectra(filterFile(od_sub, 1))
## Add an artificial peak at m/z 0 if spectrum is empty
sps <- lapply(sps, function(z) {
if (!length(z@mz)) {
z@mz <- 0.0
z@intensity <- 0.0
}
z
})
mzs <- lapply(sps, mz)
n_peaks <- lengths(mzs, FALSE)
mzs <- unlist(mzs, use.names = FALSE)
ints <- unlist(lapply(sps, intensity), use.names = FALSE)
rtms <- vapply(sps, rtime, numeric(1))
res3 <- do_findChromPeaks_matchedFilter(mz = mzs, int = ints,
scantime = rtms,
valsPerSpect = n_peaks)
full_data <- findChromPeaks(filterFile(od_x, 1),
param = MatchedFilterParam())
pks_full <- chromPeaks(full_data, mz = c(335, 344))
rownames(pks_full) <- NULL
rownames(res3) <- NULL
expect_equal(res3, pks_full[, colnames(res3)])
res4 <- findChromPeaks(filterMz(filterFile(od_x, 1), mz = c(334.9, 344.1)),
param = MatchedFilterParam())
res4 <- chromPeaks(res4)
rownames(res4) <- NULL
expect_equal(res4, pks_full)
})
test_that("peaksWithMatchedFilter is working", {
skip_on_os(os = "windows", arch = "i386")
od <- filterFile(faahko_od, file = 1)
od_mf <- findChromPeaks(od, param = MatchedFilterParam())
chr <- chromatogram(od, mz = c(272.1, 272.3))[1, 1]
pks <- peaksWithMatchedFilter(intensity(chr), rtime(chr))
pks_mf <- chromPeaks(od_mf, mz = c(272.1, 272.3))
rownames(pks_mf) <- NULL
expect_equal(pks[, "rt"], pks_mf[, "rt"])
expect_equal(pks[, "rtmin"], pks_mf[, "rtmin"])
expect_equal(pks[, "rtmax"], pks_mf[, "rtmax"])
expect_equal(pks[, "intf"], pks_mf[, "intf"])
expect_equal(pks[, "into"], pks_mf[, "into"])
expect_equal(pks[, "maxf"], pks_mf[, "maxf"])
expect_equal(pks[, "maxo"], pks_mf[, "maxo"])
## Errors and empty data.
expect_error(peaksWithMatchedFilter())
expect_error(peaksWithMatchedFilter(int = rnorm(10)))
expect_error(peaksWithMatchedFilter(int = rnorm(10)), rt = 1:4)
expect_true(nrow(peaksWithMatchedFilter(rep(NA, 10), rt = 1:10)) == 0)
})
test_that(".getRtROI works", {
skip_on_os(os = "windows", arch = "i386")
od <- filterFile(faahko_od, file = 1)
expect_error(.getRtROI())
expect_error(.getRtROI(1:3))
expect_error(.getRtROI(1:3, 1:5))
chr <- chromatogram(od, mz = c(272.1, 272.3))[1, 1]
int <- intensity(chr)
int[is.na(int)] <- 0
rt <- rtime(chr)
res <- .getRtROI(int, rt)
expect_true(is.matrix(res))
expect_true(ncol(res) == 3)
res_2 <- .getRtROI(int, rt, noise = 400)
expect_true(nrow(res) > nrow(res_2))
res_3 <- .getRtROI(int, rt, noise = 400, prefilter = c(4, 500))
expect_true(nrow(res_2) > nrow(res_3))
res_4 <- .getRtROI(int, rt, noise = 400, prefilter = c(100, 500))
expect_true(nrow(res_4) == 0)
# Generate a nice-looking peak
# Values from table(cut(rnorm(20000), breaks = 40))
model_peak <- c(3, 4, 4, 9, 26, 31, 65, 123, 196, 260, 404, 523, 743, 893,
1188, 1329, 1505, 1540, 1705, 1592, 1535, 1371, 1255, 929, 790,
652, 438, 336, 223, 138, 78, 50, 25, 15, 11, 6, 3, 0, 1, 1)
model_single_peak <- c(numeric(80), model_peak, numeric(80))
single_peak_scans <- seq_along(model_single_peak)+200
single_peak_rois <- .getRtROI(model_single_peak, single_peak_scans)
expect_true(is.matrix(single_peak_rois))
expect_true(nrow(single_peak_rois)==1)
model_triple_peak <- c(numeric(20), model_peak, numeric(100),
model_peak/5, numeric(100),
rev(model_peak)*2, numeric(20))
triple_peak_scans <- seq_along(model_triple_peak)+200
# Get ROIs for a chromatogram with 3 good peaks
triple_peak_rois <- .getRtROI(model_triple_peak, triple_peak_scans)
expect_true(nrow(triple_peak_rois)==3)
# Get ROIs for a chromatogram with three peaks
# One of which doesn't pass prefilter check
skipped_peak_rois <- .getRtROI(model_triple_peak, triple_peak_scans,
prefilter = c(3, 500))
expect_true(nrow(skipped_peak_rois)==2)
# Get ROIs for a chromatogram with three peaks
# None of which pass stringent prefilter check
skipped_peak_rois <- .getRtROI(model_triple_peak, triple_peak_scans,
prefilter = c(3, 5000))
expect_true(nrow(skipped_peak_rois)==0)
# Get ROIs for a chromatogram with three peaks
# One of which passes stringent prefilter check
tall_peak_rois <- .getRtROI(model_triple_peak, triple_peak_scans,
prefilter = c(9, 1500))
expect_true(nrow(tall_peak_rois)==1)
})
test_that("peaksWithCentWave works", {
skip_on_os(os = "windows", arch = "i386")
od <- filterFile(faahko_od, file = 1)
mzr <- c(272.1, 272.2)
od_cw <- findChromPeaks(filterMz(od, mz = c(270, 300)),
param = CentWaveParam())
chr <- chromatogram(od, mz = mzr)[1, 1]
pks <- peaksWithCentWave(intensity(chr), rtime(chr))
pks_cw <- chromPeaks(od_cw, mz = mzr)
rownames(pks_cw) <- NULL
expect_equal(pks[2, "rt"], pks_cw[, "rt"])
expect_equal(pks[2, "rtmin"], pks_cw[, "rtmin"])
expect_equal(pks[2, "rtmax"], pks_cw[, "rtmax"])
expect_equal(pks[2, "into"], pks_cw[, "into"])
cwp <- CentWaveParam(fitgauss = TRUE)
pks <- peaksWithCentWave(intensity(chr), rtime(chr), fitgauss = TRUE)
#Testing for Github issue #445 after introducing new CWP method
# Values from round((c(numeric(20), dnorm(seq(-3, 3, length.out = 20)),
# numeric(20))*100 +runif(60))*10000)
skinny_peak <- c(9107, 3326, 9523, 3245, 3429, 9394, 1123, 935, 5128, 8576,
2711, 3427, 7294, 8109, 9288, 6997, 9756, 8034, 1317, 8866, 13877,
14854, 28296, 57101, 92209, 151797, 222386, 299402, 365045, 394255,
402680, 363996, 293985, 222989, 147007, 94947, 52924, 32438,
11511, 10836, 8046, 601, 889, 5917, 2690, 5381, 9901, 8494, 3349,
8283, 3410, 5935, 3332, 7041, 3284, 7478, 76, 3739, 2158, 5507)
skinny_peak_rt <- seq_along(skinny_peak)+100
pks <- peaksWithCentWave(skinny_peak, rt=skinny_peak_rt,
snthresh = 0, peakwidth = c(20, 50),
extendLengthMSW = TRUE)
expect_true(nrow(pks)==1)
# Reducing minimum peakwidth shouldn't affect peak detection
pks_widerpeakwidth <- peaksWithCentWave(skinny_peak, rt=skinny_peak_rt,
snthresh = 0, peakwidth = c(2, 50),
extendLengthMSW = TRUE)
expect_true(nrow(pks)==nrow(pks_widerpeakwidth))
# Test a wider peak
# Values from round((dnorm(seq(-3, 3, length.out = 60))*100+runif(60))*10000)
wider_peak <- c(5000, 12043, 15344, 12748, 20730, 20781, 24673, 36956, 44600,
48596, 57698, 76937, 89422, 106482, 122977, 143989, 157769, 181563,
206296, 226309, 251067, 283592, 307523, 324212, 341520, 368568,
375716, 388428, 401694, 408352, 399415, 403964, 394144, 382952,
368333, 341668, 330255, 301146, 276234, 254643, 231601, 211038,
184239, 155817, 140996, 123284, 100121, 90280, 77303, 58708,
52817, 44003, 36068, 24637, 20688, 14162, 14836, 16603, 8341,
8307)
wider_peak_rt <- seq_along(wider_peak)+100
pks <- peaksWithCentWave(wider_peak, rt=wider_peak_rt,
snthresh = 0, peakwidth = c(20, 80),
extendLengthMSW = TRUE)
expect_true(nrow(pks)==1)
pks_widerpeakwidth <- peaksWithCentWave(skinny_peak, rt=skinny_peak_rt,
snthresh = 0, peakwidth = c(2, 80),
extendLengthMSW = TRUE)
expect_true(nrow(pks)==nrow(pks_widerpeakwidth))
## Check errors
expect_error(peaksWithCentWave())
expect_error(peaksWithCentWave(int = 1:3, rt = 1:5))
expect_warning(res <- peaksWithCentWave(int = rep(NA, 20), rt = 1:20))
expect_true(nrow(res) == 0)
})
test_that(".narrow_rt_boundaries works", {
skip_on_os(os = "windows", arch = "i386")
d <- c(0, 0, 1, 2, 1, 3, 4, 6, 4, 3, 2, 0, 1, 0, 2, 0)
## Full range
lm <- c(1, length(d))
res <- .narrow_rt_boundaries(lm, d)
expect_equal(res, c(2, 16))
res <- .narrow_rt_boundaries(lm, d, thresh = 2)
expect_equal(res, c(3, 16))
res <- .narrow_rt_boundaries(lm, d, thresh = 3)
expect_equal(res, c(5, 11))
## Subset (reflecting the real situation).
lm <- c(3, 9)
res <- .narrow_rt_boundaries(lm, d)
expect_equal(res, c(3, 9))
res <- .narrow_rt_boundaries(lm, d, thresh = 2)
expect_equal(res, c(3, 9))
res <- .narrow_rt_boundaries(lm, d, thresh = 3)
expect_equal(res, c(5, 9))
lm <- c(3, 13)
res <- .narrow_rt_boundaries(lm, d)
expect_equal(res, c(3, 13))
res <- .narrow_rt_boundaries(lm, d, thresh = 3)
expect_equal(res, c(5, 11))
## That's the fix for issue #300
expect_equal(.narrow_rt_boundaries(lm, d, thresh = 100), lm)
expect_equal(.narrow_rt_boundaries(c(1, length(d)), d, thresh = 100),
c(1, length(d)))
})
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