xcms.Rcheck/tests_i386/testthat.Rout
R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: i386-w64-mingw32/i386 (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(testthat)
> library(xcms)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: BiocParallel
Loading required package: MSnbase
Loading required package: mzR
Loading required package: Rcpp
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: ProtGenerics
This is MSnbase version 2.10.1
Visit https://lgatto.github.io/MSnbase/ to get started.
Attaching package: 'MSnbase'
The following object is masked from 'package:stats':
smooth
The following object is masked from 'package:base':
trimws
This is xcms version 3.6.2
Attaching package: 'xcms'
The following object is masked from 'package:stats':
sigma
> library(faahKO)
> library(msdata)
>
> attr(faahko, "filepaths") <- sapply(
+ as.list(basename(attr(faahko, "filepaths"))),
+ function(x) system.file("cdf", if (length(grep("ko",x)) > 0) "KO" else "WT",
+ x, package = "faahKO"))
> if (.Platform$OS.type == "unix") {
+ prm <- MulticoreParam(2)
+ } else {
+ prm <- SnowParam(2)
+ }
> register(bpstart(prm))
>
> ## Create some objects we can re-use in different tests:
> faahko_3_files <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko16.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko18.CDF', package = "faahKO"))
>
> ## An xcmsRaw for the first file:
> faahko_xr_1 <- xcmsRaw(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
+ profstep = 0)
> faahko_od <- readMSData(faahko_3_files, mode = "onDisk")
Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.
> faahko_xod <- findChromPeaks(faahko_od, param = CentWaveParam(noise = 10000,
+ snthresh = 40))
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
This is MSnbase version 2.10.1
Visit https://lgatto.github.io/MSnbase/ to get started.
Attaching package: 'MSnbase'
The following object is masked from 'package:stats':
smooth
The following object is masked from 'package:base':
trimws
This is xcms version 3.6.2
Attaching package: 'xcms'
The following object is masked from 'package:stats':
sigma
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 937 regions of interest ... OK: 87 found.
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
This is MSnbase version 2.10.1
Visit https://lgatto.github.io/MSnbase/ to get started.
Attaching package: 'MSnbase'
The following object is masked from 'package:stats':
smooth
The following object is masked from 'package:base':
trimws
This is xcms version 3.6.2
Attaching package: 'xcms'
The following object is masked from 'package:stats':
sigma
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 1025 regions of interest ... OK: 100 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 919 regions of interest ... OK: 61 found.
> faahko_xs <- xcmsSet(faahko_3_files, profparam = list(step = 0),
+ method = "centWave", noise = 10000, snthresh = 40)
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 937 regions of interest ... OK: 87 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 1025 regions of interest ... OK: 100 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 919 regions of interest ... OK: 61 found.
> faahko_xsg <- group(faahko_xs)
Processing 2572 mz slices ... OK
> ## Doing also the retention time correction etc
> od_x <- faahko_od
> mzr <- matrix(c(335, 335, 344, 344), ncol = 2, byrow = TRUE)
> od_chrs <- chromatogram(od_x, mz = mzr)
> xod_x <- faahko_xod
> pdp <- PeakDensityParam(sampleGroups = rep(1, 3))
> xod_xg <- groupChromPeaks(xod_x, param = pdp)
Processing 2572 mz slices ... OK
> xod_xgr <- adjustRtime(xod_xg, param = PeakGroupsParam(span = 0.4))
Performing retention time correction using 19 peak groups.
Applying retention time adjustment to the identified chromatographic peaks ... OK
> xod_xgrg <- groupChromPeaks(xod_xgr, param = pdp)
Processing 2572 mz slices ... OK
> xod_r <- adjustRtime(as(od_x, "XCMSnExp"), param = ObiwarpParam())
Sample number 2 used as center sample.
Aligning ko15.CDF against ko16.CDF ... OK
Aligning ko18.CDF against ko16.CDF ... OK
>
> xod_chr <- findChromPeaks(filterMz(filterRt(od_x, rt = c(2500, 3500)),
+ mz = c(334.9, 344.1)),
+ param = CentWaveParam())
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 514 regions of interest ... OK: 23 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 551 regions of interest ... OK: 29 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 515 regions of interest ... OK: 20 found.
Warning message:
In .local(object, param, ...) :
Your data appears to be not centroided! CentWave works best on data in centroid mode.
>
> faahko_grouped_filled <- fillPeaks(group(faahko))
Processing 3195 mz slices ... OK
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt22.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko22.CDF
method: bin
step: 0.1
> faahko_grouped_retcor_filled <-
+ fillPeaks(group(retcor(group(updateObject(faahko)))))
Processing 3195 mz slices ... OK
Performing retention time correction using 132 peak groups.
Processing 3195 mz slices ... OK
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt22.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko22.CDF
method: bin
step: 0.1
>
> microtofq_fs <- c(system.file("microtofq/MM14.mzML", package = "msdata"),
+ system.file("microtofq/MM8.mzML", package = "msdata"))
> microtofq_xr <- xcmsRaw(microtofq_fs[1], profstep = 0)
> microtofq_od <- readMSData(microtofq_fs, mode = "onDisk")
>
> ## Direct injection data:
> fticrf <- list.files(system.file("fticr", package = "msdata"),
+ recursive = TRUE, full.names = TRUE)
> fticr <- readMSData(fticrf[1:2], msLevel. = 1, mode = "onDisk")
> fticr_xod <- findChromPeaks(fticr, MSWParam(scales = c(1, 7),
+ peakThr = 80000, ampTh = 0.005,
+ SNR.method = "data.mean",
+ winSize.noise = 500))
> fticr_xs <- xcmsSet(method="MSW", files=fticrf[1:2], scales=c(1,7),
+ SNR.method='data.mean' , winSize.noise=500,
+ peakThr=80000, amp.Th=0.005)
>
> fs <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko16.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko18.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko19.CDF', package = "faahKO"))
> xs_1 <- xcmsSet(fs, profparam = list(step = 0), method = "centWave",
+ noise = 10000, snthresh = 50)
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 919 regions of interest ... OK: 41 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 781 regions of interest ... OK: 46 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 937 regions of interest ... OK: 75 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 1025 regions of interest ... OK: 79 found.
>
>
>
>
> test_check("xcms")
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 28.00 32.00 40.00 64.00 80.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
center sample: ko16
Processing: ko15 ko18
center sample: ko18
Processing: ko15 ko16
center sample: ko18
Processing: ko15 ko16
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 28.00 32.00 40.00 56.00 64.00 80.00 88.00 96.00 100.00
8.00 16.00 28.00 32.00 40.00 56.00 64.00 80.00 88.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
HAM004_641fE_14-11-07--Exp1.extracted HAM004_641fE_14-11-07--Exp2.extracted
Object of class: XChromatogram
length of object: 0
from file:
mz range: [NA, NA]
MS level: 1
Identified chromatographic peaks (0):
rt rtmin rtmax into maxo sn
method: bin
step: 0.1
method: bin
step: 0.3
method: binlin
step: 0.2
method: binlinbase
step: 0.2
method: intlin
step: 0.2
center sample: ko15
Processing: ko16
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
Comparing peaks...OK
Comparing peaks...OK
Comparing peaks...OK
Comparing peak groups...OK
Comparing peaks...OK
Comparing peak groups...OK
Comparing peaks...OK
Comparing peak groups...OK
== testthat results ===========================================================
[ OK: 2679 | SKIPPED: 7 | WARNINGS: 625 | FAILED: 0 ]
>
> proc.time()
user system elapsed
406.73 11.15 567.50
|
xcms.Rcheck/tests_x64/testthat.Rout
R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(testthat)
> library(xcms)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: BiocParallel
Loading required package: MSnbase
Loading required package: mzR
Loading required package: Rcpp
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: ProtGenerics
This is MSnbase version 2.10.1
Visit https://lgatto.github.io/MSnbase/ to get started.
Attaching package: 'MSnbase'
The following object is masked from 'package:stats':
smooth
The following object is masked from 'package:base':
trimws
This is xcms version 3.6.2
Attaching package: 'xcms'
The following object is masked from 'package:stats':
sigma
> library(faahKO)
> library(msdata)
>
> attr(faahko, "filepaths") <- sapply(
+ as.list(basename(attr(faahko, "filepaths"))),
+ function(x) system.file("cdf", if (length(grep("ko",x)) > 0) "KO" else "WT",
+ x, package = "faahKO"))
> if (.Platform$OS.type == "unix") {
+ prm <- MulticoreParam(2)
+ } else {
+ prm <- SnowParam(2)
+ }
> register(bpstart(prm))
>
> ## Create some objects we can re-use in different tests:
> faahko_3_files <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko16.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko18.CDF', package = "faahKO"))
>
> ## An xcmsRaw for the first file:
> faahko_xr_1 <- xcmsRaw(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
+ profstep = 0)
> faahko_od <- readMSData(faahko_3_files, mode = "onDisk")
Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.
> faahko_xod <- findChromPeaks(faahko_od, param = CentWaveParam(noise = 10000,
+ snthresh = 40))
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
This is MSnbase version 2.10.1
Visit https://lgatto.github.io/MSnbase/ to get started.
Attaching package: 'MSnbase'
The following object is masked from 'package:stats':
smooth
The following object is masked from 'package:base':
trimws
This is xcms version 3.6.2
Attaching package: 'xcms'
The following object is masked from 'package:stats':
sigma
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 937 regions of interest ... OK: 87 found.
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
This is MSnbase version 2.10.1
Visit https://lgatto.github.io/MSnbase/ to get started.
Attaching package: 'MSnbase'
The following object is masked from 'package:stats':
smooth
The following object is masked from 'package:base':
trimws
This is xcms version 3.6.2
Attaching package: 'xcms'
The following object is masked from 'package:stats':
sigma
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 1025 regions of interest ... OK: 100 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 919 regions of interest ... OK: 61 found.
> faahko_xs <- xcmsSet(faahko_3_files, profparam = list(step = 0),
+ method = "centWave", noise = 10000, snthresh = 40)
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 937 regions of interest ... OK: 87 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 1025 regions of interest ... OK: 100 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 919 regions of interest ... OK: 61 found.
> faahko_xsg <- group(faahko_xs)
Processing 2572 mz slices ... OK
> ## Doing also the retention time correction etc
> od_x <- faahko_od
> mzr <- matrix(c(335, 335, 344, 344), ncol = 2, byrow = TRUE)
> od_chrs <- chromatogram(od_x, mz = mzr)
> xod_x <- faahko_xod
> pdp <- PeakDensityParam(sampleGroups = rep(1, 3))
> xod_xg <- groupChromPeaks(xod_x, param = pdp)
Processing 2572 mz slices ... OK
> xod_xgr <- adjustRtime(xod_xg, param = PeakGroupsParam(span = 0.4))
Performing retention time correction using 19 peak groups.
Applying retention time adjustment to the identified chromatographic peaks ... OK
> xod_xgrg <- groupChromPeaks(xod_xgr, param = pdp)
Processing 2572 mz slices ... OK
> xod_r <- adjustRtime(as(od_x, "XCMSnExp"), param = ObiwarpParam())
Sample number 2 used as center sample.
Aligning ko15.CDF against ko16.CDF ... OK
Aligning ko18.CDF against ko16.CDF ... OK
>
> xod_chr <- findChromPeaks(filterMz(filterRt(od_x, rt = c(2500, 3500)),
+ mz = c(334.9, 344.1)),
+ param = CentWaveParam())
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 514 regions of interest ... OK: 23 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 551 regions of interest ... OK: 29 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 515 regions of interest ... OK: 20 found.
Warning message:
In .local(object, param, ...) :
Your data appears to be not centroided! CentWave works best on data in centroid mode.
>
> faahko_grouped_filled <- fillPeaks(group(faahko))
Processing 3195 mz slices ... OK
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt22.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko22.CDF
method: bin
step: 0.1
> faahko_grouped_retcor_filled <-
+ fillPeaks(group(retcor(group(updateObject(faahko)))))
Processing 3195 mz slices ... OK
Performing retention time correction using 132 peak groups.
Processing 3195 mz slices ... OK
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/WT/wt22.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko15.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko16.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko18.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko19.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko21.CDF
method: bin
step: 0.1
C:/Users/biocbuild/bbs-3.9-bioc/R/library/faahKO/cdf/KO/ko22.CDF
method: bin
step: 0.1
>
> microtofq_fs <- c(system.file("microtofq/MM14.mzML", package = "msdata"),
+ system.file("microtofq/MM8.mzML", package = "msdata"))
> microtofq_xr <- xcmsRaw(microtofq_fs[1], profstep = 0)
> microtofq_od <- readMSData(microtofq_fs, mode = "onDisk")
>
> ## Direct injection data:
> fticrf <- list.files(system.file("fticr", package = "msdata"),
+ recursive = TRUE, full.names = TRUE)
> fticr <- readMSData(fticrf[1:2], msLevel. = 1, mode = "onDisk")
> fticr_xod <- findChromPeaks(fticr, MSWParam(scales = c(1, 7),
+ peakThr = 80000, ampTh = 0.005,
+ SNR.method = "data.mean",
+ winSize.noise = 500))
> fticr_xs <- xcmsSet(method="MSW", files=fticrf[1:2], scales=c(1,7),
+ SNR.method='data.mean' , winSize.noise=500,
+ peakThr=80000, amp.Th=0.005)
>
> fs <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko16.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko18.CDF', package = "faahKO"),
+ system.file('cdf/KO/ko19.CDF', package = "faahKO"))
> xs_1 <- xcmsSet(fs, profparam = list(step = 0), method = "centWave",
+ noise = 10000, snthresh = 50)
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 919 regions of interest ... OK: 41 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 781 regions of interest ... OK: 46 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 937 regions of interest ... OK: 75 found.
Detecting mass traces at 25 ppm ... OK
Detecting chromatographic peaks in 1025 regions of interest ... OK: 79 found.
>
>
>
>
> test_check("xcms")
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 28.00 32.00 40.00 64.00 80.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
center sample: ko16
Processing: ko15 ko18
center sample: ko18
Processing: ko15 ko16
center sample: ko18
Processing: ko15 ko16
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 28.00 32.00 40.00 56.00 64.00 80.00 88.00 96.00 100.00
8.00 16.00 28.00 32.00 40.00 56.00 64.00 80.00 88.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
8.00 16.00 24.00 28.00 32.00 40.00 48.00 52.00 56.00 60.00 64.00 72.00 80.00 84.00 88.00 96.00 100.00
HAM004_641fE_14-11-07--Exp1.extracted HAM004_641fE_14-11-07--Exp2.extracted
Object of class: XChromatogram
length of object: 0
from file:
mz range: [NA, NA]
MS level: 1
Identified chromatographic peaks (0):
rt rtmin rtmax into maxo sn
method: bin
step: 0.1
method: bin
step: 0.3
method: binlin
step: 0.2
method: binlinbase
step: 0.2
method: intlin
step: 0.2
center sample: ko15
Processing: ko16
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
center sample: ko16
Processing: ko15
Comparing peaks...OK
Comparing peaks...OK
Comparing peaks...OK
Comparing peak groups...OK
Comparing peaks...OK
Comparing peak groups...OK
Comparing peaks...OK
Comparing peak groups...OK
== testthat results ===========================================================
[ OK: 2679 | SKIPPED: 7 | WARNINGS: 625 | FAILED: 0 ]
>
> proc.time()
user system elapsed
435.90 8.51 605.39
|