peakPantheR_parallelAnnotation: Search, integrate and report targeted features in a multiple...
In peakPantheR: Peak Picking and Annotation of High Resolution Experiments
Description
Usage
Arguments
Value
See Also
Examples
View source: R/peakPantheR_parallelAnnotation.R
Description
Integrate all target features in all files defined in the
initialised input object and store results. The use of updated ROI and the
integration of FIR are controled by the input object slots useUROI and
useFIR. Files are processed in parallel using
peakPantheR_singleFileSearch; ncores controls the number of
cores used for parallelisation, with ncores=0 corresponding to serial
processing. If the processing of a file fails (file does not exist or error
during execution) the sample is removed from the outputed object.
Usage
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peakPantheR_parallelAnnotation(
object,
ncores = 0,
getAcquTime = TRUE,
resetWorkers = 1,
centroided = TRUE,
curveModel = "skewedGaussian",
verbose = TRUE,
...
)
Arguments
object
(peakPantheRAnnotation) Initialised peakPantheRAnnotation
object defining the samples to process and compounds to target. The slots
useUROI and useFIR controls if uROI must be used and FIR
integrated if a feature is not found
ncores
(int) Number of cores to use for parallelisation. Default 0 for
no parallelisation.
getAcquTime
(bool) If TRUE will extract sample acquisition date-time
from the mzML metadata (the additional file access will impact run time)
resetWorkers
(int) If 0, the parallel cluster is only initiated once.
If >0 the cluster will be reset (and the memory of each worker freed) once
ncores * resetWorkers files have been processed. Default value is 1,
the cluster is reset once ncores files have been processed. While
potentially impacting performance (need to wait until all ncores *
resetWorkers files are processed before restarting the cluster), shutting
down the workers processes regularly will ensure the OS can reallocate memory
more efficiently. For values >1, ensure sufficient system memory is available
centroided
(bool) use TRUE if the data is centroided, used by
readMSData when reading the raw data files
curveModel
(str) specify the peak-shape model to fit,
by default skewedGaussian.
Accepted values are skewedGaussian and emgGaussian
verbose
(bool) If TRUE message calculation progress, time taken,
number of features found (total and matched to targets) and failures
...
Passes arguments to findTargetFeatures to alter
peak-picking parameters
Value
a list: list()$result (peakPantheRAnnotation) fully
annotated object, list()$failures (list) list of failed samples
and error message
See Also
Other peakPantheR:
peakPantheRAnnotation,
peakPantheR_singleFileSearch()
Other parallelAnnotation:
peakPantheRAnnotation,
peakPantheR_singleFileSearch()
Examples
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if(requireNamespace('faahKO')){
## Load data
library(faahKO)
# 3 files
input_spectraPaths <- 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'))
# 4 features
input_ROI <- data.frame(matrix(vector(), 4, 8,
dimnames=list(c(), c('cpdID', 'cpdName', 'rtMin', 'rt',
'rtMax', 'mzMin', 'mz', 'mzMax'))),
stringsAsFactors=FALSE)
input_ROI[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
522.2, 522.205222)
input_ROI[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
496.2, 496.204962)
input_ROI[3,] <- c('ID-3', 'Cpd 3', 3420., 3454.435, 3495., 464.195358,
464.2, 464.204642)
input_ROI[4,] <- c('ID-4', 'Cpd 4', 3670., 3701.697, 3745., 536.194638,
536.2, 536.205362)
input_ROI[,c(3:8)] <- vapply(input_ROI[,c(3:8)], as.numeric,
FUN.VALUE=numeric(4))
# Initialise object
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths,
targetFeatTable=input_ROI)
# to use updated ROI:
# uROIExist=TRUE, useUROI=TRUE, uROI=input_uROI
# to use FallBack Integration Regions:
# useFIR=TRUE, FIR=input_FIR
# Run serially
result_parallelAnnotation <- peakPantheR_parallelAnnotation(initAnnotation,
ncores=0,
getAcquTime=FALSE,
verbose=TRUE)
# Processing 4 compounds in 3 samples:
# uROI:\tFALSE
# FIR:\tFALSE
# ----- ko15 -----
# Polarity can not be extracted from netCDF files, please set manually the
# polarity with the 'polarity' method.
# Reading data from 4 windows
# Data read in: 0.24 secs
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #1
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #3
# Found 4/4 features in 0.06 secs
# Peak statistics done in: 0.02 secs
# Feature search done in: 0.76 secs
# ----- ko16 -----
# Polarity can not be extracted from netCDF files, please set manually the
# polarity with the 'polarity' method.
# Reading data from 4 windows
# Data read in: 0.24 secs
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #1
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #2
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #3
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #4
# Found 4/4 features in 0.08 secs
# Peak statistics done in: 0 secs
# Feature search done in: 0.71 secs
# ----- ko18 -----
# Polarity can not be extracted from netCDF files, please set manually the
# polarity with the 'polarity' method.
# Reading data from 4 windows
# Data read in: 0.25 secs
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #1
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #2
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #4
# Found 4/4 features in 0.06 secs
# Peak statistics done in: 0 secs
# Feature search done in: 0.71 secs
# ----------------
# Parallel annotation done in: 2.18 secs
# No failures
result_parallelAnnotation$failures
result_parallelAnnotation$annotation
# An object of class peakPantheRAnnotation
# 4 compounds in 3 samples.
# updated ROI do not exist (uROI)
# does not use updated ROI (uROI)
# does not use fallback integration regions (FIR)
# is annotated
}
peakPantheR documentation built on Nov. 8, 2020, 6:38 p.m.
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Description Usage Arguments Value See Also Examples
View source: R/peakPantheR_parallelAnnotation.R
Description
Integrate all target features in all files defined in the
initialised input object and store results. The use of updated ROI and the
integration of FIR are controled by the input object slots useUROI and
useFIR. Files are processed in parallel using
peakPantheR_singleFileSearch; ncores controls the number of
cores used for parallelisation, with ncores=0 corresponding to serial
processing. If the processing of a file fails (file does not exist or error
during execution) the sample is removed from the outputed object.
Usage
1 2 3 4 5 6 7 8 9 10 | peakPantheR_parallelAnnotation(
object,
ncores = 0,
getAcquTime = TRUE,
resetWorkers = 1,
centroided = TRUE,
curveModel = "skewedGaussian",
verbose = TRUE,
...
)
|
Arguments
object |
(peakPantheRAnnotation) Initialised peakPantheRAnnotation
object defining the samples to process and compounds to target. The slots
|
ncores |
(int) Number of cores to use for parallelisation. Default 0 for no parallelisation. |
getAcquTime |
(bool) If TRUE will extract sample acquisition date-time from the mzML metadata (the additional file access will impact run time) |
resetWorkers |
(int) If 0, the parallel cluster is only initiated once.
If >0 the cluster will be reset (and the memory of each worker freed) once
|
centroided |
(bool) use TRUE if the data is centroided, used by
|
curveModel |
(str) specify the peak-shape model to fit,
by default |
verbose |
(bool) If TRUE message calculation progress, time taken, number of features found (total and matched to targets) and failures |
... |
Passes arguments to |
Value
a list: list()$result (peakPantheRAnnotation) fully
annotated object, list()$failures (list) list of failed samples
and error message
See Also
Other peakPantheR:
peakPantheRAnnotation,
peakPantheR_singleFileSearch()
Other parallelAnnotation:
peakPantheRAnnotation,
peakPantheR_singleFileSearch()
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 | if(requireNamespace('faahKO')){
## Load data
library(faahKO)
# 3 files
input_spectraPaths <- 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'))
# 4 features
input_ROI <- data.frame(matrix(vector(), 4, 8,
dimnames=list(c(), c('cpdID', 'cpdName', 'rtMin', 'rt',
'rtMax', 'mzMin', 'mz', 'mzMax'))),
stringsAsFactors=FALSE)
input_ROI[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
522.2, 522.205222)
input_ROI[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
496.2, 496.204962)
input_ROI[3,] <- c('ID-3', 'Cpd 3', 3420., 3454.435, 3495., 464.195358,
464.2, 464.204642)
input_ROI[4,] <- c('ID-4', 'Cpd 4', 3670., 3701.697, 3745., 536.194638,
536.2, 536.205362)
input_ROI[,c(3:8)] <- vapply(input_ROI[,c(3:8)], as.numeric,
FUN.VALUE=numeric(4))
# Initialise object
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths,
targetFeatTable=input_ROI)
# to use updated ROI:
# uROIExist=TRUE, useUROI=TRUE, uROI=input_uROI
# to use FallBack Integration Regions:
# useFIR=TRUE, FIR=input_FIR
# Run serially
result_parallelAnnotation <- peakPantheR_parallelAnnotation(initAnnotation,
ncores=0,
getAcquTime=FALSE,
verbose=TRUE)
# Processing 4 compounds in 3 samples:
# uROI:\tFALSE
# FIR:\tFALSE
# ----- ko15 -----
# Polarity can not be extracted from netCDF files, please set manually the
# polarity with the 'polarity' method.
# Reading data from 4 windows
# Data read in: 0.24 secs
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #1
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #3
# Found 4/4 features in 0.06 secs
# Peak statistics done in: 0.02 secs
# Feature search done in: 0.76 secs
# ----- ko16 -----
# Polarity can not be extracted from netCDF files, please set manually the
# polarity with the 'polarity' method.
# Reading data from 4 windows
# Data read in: 0.24 secs
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #1
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #2
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #3
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #4
# Found 4/4 features in 0.08 secs
# Peak statistics done in: 0 secs
# Feature search done in: 0.71 secs
# ----- ko18 -----
# Polarity can not be extracted from netCDF files, please set manually the
# polarity with the 'polarity' method.
# Reading data from 4 windows
# Data read in: 0.25 secs
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #1
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #2
# Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for
# mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and
# ROI$mzMax for ROI #4
# Found 4/4 features in 0.06 secs
# Peak statistics done in: 0 secs
# Feature search done in: 0.71 secs
# ----------------
# Parallel annotation done in: 2.18 secs
# No failures
result_parallelAnnotation$failures
result_parallelAnnotation$annotation
# An object of class peakPantheRAnnotation
# 4 compounds in 3 samples.
# updated ROI do not exist (uROI)
# does not use updated ROI (uROI)
# does not use fallback integration regions (FIR)
# is annotated
}
|
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