tests/testthat/test_align_dia_runs.R
In shubham1637/DIAlignR: Dynamic Programming Based Alignment of MS2 Chromatograms
context("Align DIA runs")
test_that("test_alignTargetedRuns",{
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["XICfilter"]] <- "none"
params[["globalAlignment"]] <- "loess"
params[["context"]] <- "experiment-wide"
params[["baseSubtraction"]] <- TRUE
expect_message(
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
runs = NULL, applyFun = lapply)
)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 4:10){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
runs <- c("hroest_K120808_Strep10%PlasmaBiolRepl1_R03_SW_filt",
"hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt")
BiocParallel::register(BiocParallel::MulticoreParam())
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["batchSize"]] <- 10L
params[["globalAlignment"]] <- "loess"
params[["context"]] <- "experiment-wide"
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
runs = runs, applyFun = lapply)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test2.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 4:14){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["XICfilter"]] <- "none"
params[["context"]] <- "experiment-wide"
params[["transitionIntensity"]] <- TRUE
params[["globalAlignment"]] <- "linear"
params[["baseSubtraction"]] <- TRUE
expect_message(
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
runs = NULL, applyFun = lapply)
)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
x <- sapply(outData[["intensity"]], function(a) sum(as.numeric(strsplit(a, split = ",")[[1]])), USE.NAMES = FALSE)
expect_equal(x, expData[["intensity"]], tolerance = 1e-04)
for(i in 6:10){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["context"]] <- "experiment-wide"
peps <- c(8496L, 15879L, 19800L)
params[["transitionIntensity"]] <- TRUE
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
refRun = "hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt",
runs = NULL, peps = peps, applyFun = lapply)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test4.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
expect_equal(outData[["RT"]], expData[["RT"]], tolerance = 1e-04)
x <- sapply(outData[["intensity"]], function(a) sum(as.numeric(strsplit(a, split = ",")[[1]])), USE.NAMES = FALSE)
y <- sapply(expData[["intensity"]], function(a) sum(as.numeric(strsplit(a, split = ",")[[1]])), USE.NAMES = FALSE)
expect_equal(x, y, tolerance = 1e-04)
for(i in 6:10){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
})
test_that("test_getAlignObjs",{
runs <- c("hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt", "hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt")
refRun <- "hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt"
dataPath <- system.file("extdata", package = "DIAlignR")
analytes <- c(32L, 898L, 4618L)
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["globalAlignment"]] <- "loess"
params[["kernelLen"]] <- 13L
params[["polyOrd"]] <- 4L
params[["context"]] <- "experiment-wide"
params[["chromFile"]] <- "mzML"
expect_warning(
outData <- getAlignObjs(analytes, runs, dataPath = dataPath, refRun = refRun,
oswMerged = TRUE, params = params, objType = "light")
)
expData <- testAlignObj()
expect_equal(outData[[2]][["4618"]][["run1_run2"]][[1]], expData, tolerance = 1e-05)
data(XIC_QFNNTDIVLLEDFQK_3_DIAlignR, package="DIAlignR")
XICs <- XIC_QFNNTDIVLLEDFQK_3_DIAlignR
expect_equal(outData[[2]][["4618"]][["run1_run2"]][["ref"]],
lapply(XICs[["hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix), tolerance = 1e-05)
expect_equal(outData[[2]][["4618"]][["run1_run2"]][["eXp"]],
lapply(XICs[["hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix), tolerance = 1e-05)
expData <- data.frame("leftWidth" = 5220.758, "RT" = 5238.35, "rightWidth" = 5261.723)
expect_equal(as.data.frame(outData[[2]][["4618"]][["run1_run2"]][["peak"]]), expData, tolerance = 1e-05)
expect_identical(outData[[2]][["32"]], NULL)
expect_identical(outData[[2]][["898"]], NULL)
})
test_that("test_alignTargetedRuns_metabolomics",{
dataPath <- system.file("metabo", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxFdrQuery"]] <- 0.05
params[["unalignedFDR"]] <- 0.05
params[["alignedFDR2"]] <- 0.05
params[["analyteFDR"]] <- 1.0
params[["maxPeptideFdr"]] <- 0.05
params[["kernelLen"]] <- 9L
params[["globalAlignment"]] <- "linear"
params[["globalAlignmentFdr"]] <- 0.05
params[["context"]] <- "experiment-wide"
params[["runType"]] <- "DIA_Metabolomics"
params[["samples4gradient"]] <- 100L
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp_metabo", params = params,
oswMerged = TRUE, runs = NULL, applyFun = lapply)
outData <- read.table("temp_metabo.tsv", sep = "\t", header = TRUE)
expData <- read.table("test_metabo.tsv", sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide"]], expData[["peptide"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 1:13){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp_metabo.tsv")
})
test_that("test_alignTargetedRuns_ptms",{
dataPath <- system.file("ptms", package = "DIAlignR")
params <- paramsDIAlignR()
params$chromFile <- "sqMass"
params$runType <- "DIA_IPF"
params$maxFdrQuery <- 0.05
params$maxIPFFdrQuery <- 1
params$useIdentifying <- TRUE
params$unalignedFDR <- 0.05
params$alignedFDR2 <- 0.05
params$globalAlignment <- "linear"
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp_ptms", params = params,
oswMerged = TRUE, runs = NULL, applyFun = lapply)
outData <- read.table("temp_ptms.tsv", sep = "\t", header = TRUE)
expData <- read.table("temp_ptms.tsv", sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide"]], expData[["peptide"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 1:13){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp_ptms.tsv")
})
test_that("test_alignToRef",{
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["unalignedFDR"]] <- 0.01
params[["context"]] <- "experiment-wide"
params$kernelLen <- 13L
params[["globalAlignment"]] <- "linear"
params[["globalAlignmentFdr"]] <- 0.05
params[["baseSubtraction"]] <- TRUE
fileInfo <- getRunNames(dataPath, oswMerged = TRUE, params)
precursors <- getPrecursors(fileInfo, oswMerged= TRUE, params[["runType"]], params[["context"]], params[["maxPeptideFdr"]])
precursors <- precursors[precursors$peptide_id %in% c("7040", "9861", "14383"),]
mzPntrs <- getMZMLpointers(fileInfo)
prec2chromIndex <- getChromatogramIndices(fileInfo, precursors, mzPntrs)
features <- getFeatures(fileInfo, maxFdrQuery = 0.05)
refRuns <- data.table("peptide_id" = c("7040", "14383", "9861"), "run" = "run1", key = "peptide_id")
globalFits <- getGlobalFits(refRuns, features, fileInfo, params[["globalAlignment"]],
params[["globalAlignmentFdr"]], params[["globalAlignmentSpan"]])
RSE <- list()
RSE[["run1_run2"]] <- 38.6594179136227/params$RSEdistFactor
globalFits <- lapply(globalFits, extractFit, params[["globalAlignment"]])
data(XIC_QFNNTDIVLLEDFQK_3_DIAlignR, package="DIAlignR")
data(multipeptide_DIAlignR, package="DIAlignR")
# Case 1
df <- data.table::copy(multipeptide_DIAlignR[["14383"]])
df$alignment_rank[3] <- 1L; df$m_score[5] <- 0.06
XICs.ref <- list(); XICs <- list(); XICs[["run2"]] <- list()
XICs.ref[["4618"]] <- lapply(XIC_QFNNTDIVLLEDFQK_3_DIAlignR[["hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix)
XICs[[1]][["4618"]] <- lapply(XIC_QFNNTDIVLLEDFQK_3_DIAlignR[["hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix)
alignToRef(eXp = "run2", ref = "run1", refIdx= 3L, fileInfo, XICs, XICs.ref, params, df, globalFits, RSE)
expect_equal(df[6,], data.table("transition_group_id" = 4618L, feature_id = bit64::NA_integer64_,
RT = 5241.30, intensity = 189.304, leftWidth = 5224.2, rightWidth = 5265.2, peak_group_rank = NA_integer_,
m_score = NA_real_, run = "run2", alignment_rank = 1, key = "run"),
tolerance = 1e-06)
# Case 2
df <- data.table::copy(multipeptide_DIAlignR[["14383"]])
df$alignment_rank[3] <- 1L
alignToRef(eXp = "run2", ref = "run1", refIdx = 3L, fileInfo, NULL, NULL, params, df, globalFits, RSE)
expect_equal(df[c(5,6), alignment_rank], c(1L, NA_integer_))
# Case 3
params[["chromFile"]] <- "mzML"
chromIndices <- prec2chromIndex[["run1"]][c(2,3), chromatogramIndex]
mz <- mzR::openMSfile(file.path(dataPath, "xics","hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt.chrom.mzML"))
XICs.ref <- lapply(chromIndices, function(i) extractXIC_group(mz, chromIndices = i+1)) # sqMass file indices start with 0, mzML start with 1
names(XICs.ref) <- c("9719", "9720")
chromIndices <- prec2chromIndex[["run2"]][c(2,3), chromatogramIndex]
mz <- mzR::openMSfile(file.path(dataPath, "xics","hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt.chrom.mzML"))
xics <- lapply(chromIndices, function(i) extractXIC_group(mz, chromIndices = i+1)) # sqMass file indices start with 0, mzML start with 1
names(xics) <- c("9719", "9720")
XICs <- list(); XICs[["run2"]] <- xics
df <- multipeptide_DIAlignR[["9861"]]
df$alignment_rank[6] <- 1L
alignToRef(eXp = "run2", ref = "run1", refIdx = 6L, fileInfo, XICs, XICs.ref, params, df, globalFits, RSE)
expect_equal(df[10,alignment_rank],1L)
expect_equal(df[9,], data.table("transition_group_id" = 9719L, feature_id = bit64::NA_integer64_,
RT = 2607.05, intensity = 11.80541, leftWidth = 2591.431, rightWidth = 2625.569, peak_group_rank = NA_integer_,
m_score = NA_real_, run = "run2", alignment_rank = 1, key = "run"),
tolerance = 1e-06)
# Case 4
df <- data.table::copy(multipeptide_DIAlignR[["7040"]])
expect_message(alignToRef(eXp = "run2", ref = "run1", refIdx = integer(0), fileInfo, NULL, NULL,
params, df, globalFits, RSE))
for(con in mzPntrs) DBI::dbDisconnect(con)
})
test_that("test_perBatch",{
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["context"]] <- "experiment-wide"
params[["baseSubtraction"]] <- TRUE
params$kernelLen <- 13L
params[["globalAlignmentFdr"]] <- 0.05
params[["maxPeptideFdr"]] <- 0.05
params$batchSize <- 1L
fileInfo <- getRunNames(dataPath, oswMerged = TRUE, params)
precursors <- getPrecursors(fileInfo, oswMerged= TRUE, params[["runType"]], params[["context"]], params[["maxPeptideFdr"]])
precursors <- precursors[precursors$peptide_id %in% c("7040", "9861", "14383"),]
peptideIDs <- c(7040L, 9861L, 14383L)
mzPntrs <- getMZMLpointers(fileInfo)
prec2chromIndex <- getChromatogramIndices(fileInfo, precursors, mzPntrs)
features <- getFeatures(fileInfo, maxFdrQuery = 0.05)
multipeptide <- getMultipeptide(precursors, features)
refRuns <- data.frame("peptide_id" = c("7040", "9861", "14383"), "run" = "run1")
globalFits <- getGlobalFits(refRuns, features, fileInfo, params[["globalAlignment"]],
params[["globalAlignmentFdr"]], params[["globalAlignmentSpan"]])
RSE <- list()
RSE[["run1_run2"]] <- RSE[["run1_run0"]] <- 38.6594179136227/params$RSEdistFactor
globalFits <- lapply(globalFits, extractFit, params[["globalAlignment"]])
# Case 1 Missing chromatograms
df <- data.table::copy(multipeptide[["7040"]])
expect_message(perBatch(iBatch = 1L, peptideIDs, multipeptide, refRuns, precursors,
prec2chromIndex, fileInfo, mzPntrs, params, globalFits, RSE))
expect_equal(df, multipeptide[["7040"]])
# Case 2
df <- data.table::copy(multipeptide[["14383"]])
perBatch(iBatch = 3L, peptideIDs, multipeptide, refRuns, precursors, prec2chromIndex, fileInfo,
mzPntrs, params, globalFits, RSE)
df$alignment_rank[c(1,3,5)] <- 1L
expect_equal(multipeptide[["14383"]], df)
# Case 3
df <- data.table::copy(multipeptide[["9861"]])
perBatch(iBatch = 2L, peptideIDs, multipeptide, refRuns, precursors,
prec2chromIndex, fileInfo, mzPntrs, params, globalFits, RSE)
data.table::set(df, 1L, c(3L,4L,5L,6L), list(2541.83, 12.92301, 2526.555, 2560.693))
data.table::set(df, 9L, c(3L,4L,5L,6L), list(2607.05, 11.80541, 2591.431, 2625.569))
df$alignment_rank[c(1,2,5,6,9,10)] <- 1L
expect_equal(df, multipeptide[["9861"]], tolerance = 1e-06)
for(con in mzPntrs) DBI::dbDisconnect(con)
})
shubham1637/DIAlignR documentation built on March 29, 2023, 8:45 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
context("Align DIA runs")
test_that("test_alignTargetedRuns",{
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["XICfilter"]] <- "none"
params[["globalAlignment"]] <- "loess"
params[["context"]] <- "experiment-wide"
params[["baseSubtraction"]] <- TRUE
expect_message(
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
runs = NULL, applyFun = lapply)
)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 4:10){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
runs <- c("hroest_K120808_Strep10%PlasmaBiolRepl1_R03_SW_filt",
"hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt")
BiocParallel::register(BiocParallel::MulticoreParam())
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["batchSize"]] <- 10L
params[["globalAlignment"]] <- "loess"
params[["context"]] <- "experiment-wide"
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
runs = runs, applyFun = lapply)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test2.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 4:14){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["XICfilter"]] <- "none"
params[["context"]] <- "experiment-wide"
params[["transitionIntensity"]] <- TRUE
params[["globalAlignment"]] <- "linear"
params[["baseSubtraction"]] <- TRUE
expect_message(
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
runs = NULL, applyFun = lapply)
)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
x <- sapply(outData[["intensity"]], function(a) sum(as.numeric(strsplit(a, split = ",")[[1]])), USE.NAMES = FALSE)
expect_equal(x, expData[["intensity"]], tolerance = 1e-04)
for(i in 6:10){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["context"]] <- "experiment-wide"
peps <- c(8496L, 15879L, 19800L)
params[["transitionIntensity"]] <- TRUE
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp", params = params, oswMerged = TRUE,
refRun = "hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt",
runs = NULL, peps = peps, applyFun = lapply)
outData <- read.table("temp.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expData <- read.table("test4.tsv", stringsAsFactors = FALSE, sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide_id"]], expData[["peptide_id"]])
expect_identical(outData[["precursor"]], expData[["precursor"]])
expect_identical(outData[["run"]], expData[["run"]])
expect_equal(outData[["RT"]], expData[["RT"]], tolerance = 1e-04)
x <- sapply(outData[["intensity"]], function(a) sum(as.numeric(strsplit(a, split = ",")[[1]])), USE.NAMES = FALSE)
y <- sapply(expData[["intensity"]], function(a) sum(as.numeric(strsplit(a, split = ",")[[1]])), USE.NAMES = FALSE)
expect_equal(x, y, tolerance = 1e-04)
for(i in 6:10){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp.tsv")
})
test_that("test_getAlignObjs",{
runs <- c("hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt", "hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt")
refRun <- "hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt"
dataPath <- system.file("extdata", package = "DIAlignR")
analytes <- c(32L, 898L, 4618L)
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["globalAlignment"]] <- "loess"
params[["kernelLen"]] <- 13L
params[["polyOrd"]] <- 4L
params[["context"]] <- "experiment-wide"
params[["chromFile"]] <- "mzML"
expect_warning(
outData <- getAlignObjs(analytes, runs, dataPath = dataPath, refRun = refRun,
oswMerged = TRUE, params = params, objType = "light")
)
expData <- testAlignObj()
expect_equal(outData[[2]][["4618"]][["run1_run2"]][[1]], expData, tolerance = 1e-05)
data(XIC_QFNNTDIVLLEDFQK_3_DIAlignR, package="DIAlignR")
XICs <- XIC_QFNNTDIVLLEDFQK_3_DIAlignR
expect_equal(outData[[2]][["4618"]][["run1_run2"]][["ref"]],
lapply(XICs[["hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix), tolerance = 1e-05)
expect_equal(outData[[2]][["4618"]][["run1_run2"]][["eXp"]],
lapply(XICs[["hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix), tolerance = 1e-05)
expData <- data.frame("leftWidth" = 5220.758, "RT" = 5238.35, "rightWidth" = 5261.723)
expect_equal(as.data.frame(outData[[2]][["4618"]][["run1_run2"]][["peak"]]), expData, tolerance = 1e-05)
expect_identical(outData[[2]][["32"]], NULL)
expect_identical(outData[[2]][["898"]], NULL)
})
test_that("test_alignTargetedRuns_metabolomics",{
dataPath <- system.file("metabo", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxFdrQuery"]] <- 0.05
params[["unalignedFDR"]] <- 0.05
params[["alignedFDR2"]] <- 0.05
params[["analyteFDR"]] <- 1.0
params[["maxPeptideFdr"]] <- 0.05
params[["kernelLen"]] <- 9L
params[["globalAlignment"]] <- "linear"
params[["globalAlignmentFdr"]] <- 0.05
params[["context"]] <- "experiment-wide"
params[["runType"]] <- "DIA_Metabolomics"
params[["samples4gradient"]] <- 100L
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp_metabo", params = params,
oswMerged = TRUE, runs = NULL, applyFun = lapply)
outData <- read.table("temp_metabo.tsv", sep = "\t", header = TRUE)
expData <- read.table("test_metabo.tsv", sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide"]], expData[["peptide"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 1:13){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp_metabo.tsv")
})
test_that("test_alignTargetedRuns_ptms",{
dataPath <- system.file("ptms", package = "DIAlignR")
params <- paramsDIAlignR()
params$chromFile <- "sqMass"
params$runType <- "DIA_IPF"
params$maxFdrQuery <- 0.05
params$maxIPFFdrQuery <- 1
params$useIdentifying <- TRUE
params$unalignedFDR <- 0.05
params$alignedFDR2 <- 0.05
params$globalAlignment <- "linear"
params[["baseSubtraction"]] <- TRUE
alignTargetedRuns(dataPath = dataPath, outFile = "temp_ptms", params = params,
oswMerged = TRUE, runs = NULL, applyFun = lapply)
outData <- read.table("temp_ptms.tsv", sep = "\t", header = TRUE)
expData <- read.table("temp_ptms.tsv", sep = "\t", header = TRUE)
expect_identical(dim(outData), dim(expData))
expect_identical(colnames(outData), colnames(expData))
expect_identical(outData[["peptide"]], expData[["peptide"]])
expect_identical(outData[["run"]], expData[["run"]])
for(i in 1:13){
expect_equal(outData[[i]], expData[[i]], tolerance = 1e-04)
}
file.remove("temp_ptms.tsv")
})
test_that("test_alignToRef",{
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["maxPeptideFdr"]] <- 0.05
params[["unalignedFDR"]] <- 0.01
params[["context"]] <- "experiment-wide"
params$kernelLen <- 13L
params[["globalAlignment"]] <- "linear"
params[["globalAlignmentFdr"]] <- 0.05
params[["baseSubtraction"]] <- TRUE
fileInfo <- getRunNames(dataPath, oswMerged = TRUE, params)
precursors <- getPrecursors(fileInfo, oswMerged= TRUE, params[["runType"]], params[["context"]], params[["maxPeptideFdr"]])
precursors <- precursors[precursors$peptide_id %in% c("7040", "9861", "14383"),]
mzPntrs <- getMZMLpointers(fileInfo)
prec2chromIndex <- getChromatogramIndices(fileInfo, precursors, mzPntrs)
features <- getFeatures(fileInfo, maxFdrQuery = 0.05)
refRuns <- data.table("peptide_id" = c("7040", "14383", "9861"), "run" = "run1", key = "peptide_id")
globalFits <- getGlobalFits(refRuns, features, fileInfo, params[["globalAlignment"]],
params[["globalAlignmentFdr"]], params[["globalAlignmentSpan"]])
RSE <- list()
RSE[["run1_run2"]] <- 38.6594179136227/params$RSEdistFactor
globalFits <- lapply(globalFits, extractFit, params[["globalAlignment"]])
data(XIC_QFNNTDIVLLEDFQK_3_DIAlignR, package="DIAlignR")
data(multipeptide_DIAlignR, package="DIAlignR")
# Case 1
df <- data.table::copy(multipeptide_DIAlignR[["14383"]])
df$alignment_rank[3] <- 1L; df$m_score[5] <- 0.06
XICs.ref <- list(); XICs <- list(); XICs[["run2"]] <- list()
XICs.ref[["4618"]] <- lapply(XIC_QFNNTDIVLLEDFQK_3_DIAlignR[["hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix)
XICs[[1]][["4618"]] <- lapply(XIC_QFNNTDIVLLEDFQK_3_DIAlignR[["hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt"]][["4618"]], as.matrix)
alignToRef(eXp = "run2", ref = "run1", refIdx= 3L, fileInfo, XICs, XICs.ref, params, df, globalFits, RSE)
expect_equal(df[6,], data.table("transition_group_id" = 4618L, feature_id = bit64::NA_integer64_,
RT = 5241.30, intensity = 189.304, leftWidth = 5224.2, rightWidth = 5265.2, peak_group_rank = NA_integer_,
m_score = NA_real_, run = "run2", alignment_rank = 1, key = "run"),
tolerance = 1e-06)
# Case 2
df <- data.table::copy(multipeptide_DIAlignR[["14383"]])
df$alignment_rank[3] <- 1L
alignToRef(eXp = "run2", ref = "run1", refIdx = 3L, fileInfo, NULL, NULL, params, df, globalFits, RSE)
expect_equal(df[c(5,6), alignment_rank], c(1L, NA_integer_))
# Case 3
params[["chromFile"]] <- "mzML"
chromIndices <- prec2chromIndex[["run1"]][c(2,3), chromatogramIndex]
mz <- mzR::openMSfile(file.path(dataPath, "xics","hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt.chrom.mzML"))
XICs.ref <- lapply(chromIndices, function(i) extractXIC_group(mz, chromIndices = i+1)) # sqMass file indices start with 0, mzML start with 1
names(XICs.ref) <- c("9719", "9720")
chromIndices <- prec2chromIndex[["run2"]][c(2,3), chromatogramIndex]
mz <- mzR::openMSfile(file.path(dataPath, "xics","hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt.chrom.mzML"))
xics <- lapply(chromIndices, function(i) extractXIC_group(mz, chromIndices = i+1)) # sqMass file indices start with 0, mzML start with 1
names(xics) <- c("9719", "9720")
XICs <- list(); XICs[["run2"]] <- xics
df <- multipeptide_DIAlignR[["9861"]]
df$alignment_rank[6] <- 1L
alignToRef(eXp = "run2", ref = "run1", refIdx = 6L, fileInfo, XICs, XICs.ref, params, df, globalFits, RSE)
expect_equal(df[10,alignment_rank],1L)
expect_equal(df[9,], data.table("transition_group_id" = 9719L, feature_id = bit64::NA_integer64_,
RT = 2607.05, intensity = 11.80541, leftWidth = 2591.431, rightWidth = 2625.569, peak_group_rank = NA_integer_,
m_score = NA_real_, run = "run2", alignment_rank = 1, key = "run"),
tolerance = 1e-06)
# Case 4
df <- data.table::copy(multipeptide_DIAlignR[["7040"]])
expect_message(alignToRef(eXp = "run2", ref = "run1", refIdx = integer(0), fileInfo, NULL, NULL,
params, df, globalFits, RSE))
for(con in mzPntrs) DBI::dbDisconnect(con)
})
test_that("test_perBatch",{
dataPath <- system.file("extdata", package = "DIAlignR")
params <- paramsDIAlignR()
params[["context"]] <- "experiment-wide"
params[["baseSubtraction"]] <- TRUE
params$kernelLen <- 13L
params[["globalAlignmentFdr"]] <- 0.05
params[["maxPeptideFdr"]] <- 0.05
params$batchSize <- 1L
fileInfo <- getRunNames(dataPath, oswMerged = TRUE, params)
precursors <- getPrecursors(fileInfo, oswMerged= TRUE, params[["runType"]], params[["context"]], params[["maxPeptideFdr"]])
precursors <- precursors[precursors$peptide_id %in% c("7040", "9861", "14383"),]
peptideIDs <- c(7040L, 9861L, 14383L)
mzPntrs <- getMZMLpointers(fileInfo)
prec2chromIndex <- getChromatogramIndices(fileInfo, precursors, mzPntrs)
features <- getFeatures(fileInfo, maxFdrQuery = 0.05)
multipeptide <- getMultipeptide(precursors, features)
refRuns <- data.frame("peptide_id" = c("7040", "9861", "14383"), "run" = "run1")
globalFits <- getGlobalFits(refRuns, features, fileInfo, params[["globalAlignment"]],
params[["globalAlignmentFdr"]], params[["globalAlignmentSpan"]])
RSE <- list()
RSE[["run1_run2"]] <- RSE[["run1_run0"]] <- 38.6594179136227/params$RSEdistFactor
globalFits <- lapply(globalFits, extractFit, params[["globalAlignment"]])
# Case 1 Missing chromatograms
df <- data.table::copy(multipeptide[["7040"]])
expect_message(perBatch(iBatch = 1L, peptideIDs, multipeptide, refRuns, precursors,
prec2chromIndex, fileInfo, mzPntrs, params, globalFits, RSE))
expect_equal(df, multipeptide[["7040"]])
# Case 2
df <- data.table::copy(multipeptide[["14383"]])
perBatch(iBatch = 3L, peptideIDs, multipeptide, refRuns, precursors, prec2chromIndex, fileInfo,
mzPntrs, params, globalFits, RSE)
df$alignment_rank[c(1,3,5)] <- 1L
expect_equal(multipeptide[["14383"]], df)
# Case 3
df <- data.table::copy(multipeptide[["9861"]])
perBatch(iBatch = 2L, peptideIDs, multipeptide, refRuns, precursors,
prec2chromIndex, fileInfo, mzPntrs, params, globalFits, RSE)
data.table::set(df, 1L, c(3L,4L,5L,6L), list(2541.83, 12.92301, 2526.555, 2560.693))
data.table::set(df, 9L, c(3L,4L,5L,6L), list(2607.05, 11.80541, 2591.431, 2625.569))
df$alignment_rank[c(1,2,5,6,9,10)] <- 1L
expect_equal(df, multipeptide[["9861"]], tolerance = 1e-06)
for(con in mzPntrs) DBI::dbDisconnect(con)
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.