Export data tables from Binalysis,MetaboProfile, Analysis and Assignment classes.
Usage
exportData(x, outPath = ".", ...)
# S4 method for Binalysis
exportData(x, outPath = ".")
# S4 method for MetaboProfile
exportData(x, outPath = ".")
# S4 method for AnalysisData
exportData(x, outPath = ".", idx = "name", prefix = "analysis")
# S4 method for Analysis
exportData(x, outPath = ".", type = "raw", idx = "name")
# S4 method for Assignment
exportData(x, outPath = ".")
exportSampleInfo(x, outPath = ".", ...)
# S4 method for Binalysis
exportSampleInfo(x, outPath = ".")
# S4 method for MetaboProfile
exportSampleInfo(x, outPath = ".")
# S4 method for AnalysisData
exportSampleInfo(x, outPath = ".", prefix = "analysis")
# S4 method for Analysis
exportSampleInfo(x, outPath = ".", type = "raw")
exportAccurateData(x, outPath = ".")
# S4 method for Binalysis
exportAccurateData(x, outPath = ".")
exportPeakInfo(x, outPath = ".")
# S4 method for MetaboProfile
exportPeakInfo(x, outPath = ".")
exportModellingMetrics(x, outPath = ".")
# S4 method for Analysis
exportModellingMetrics(x, outPath = ".")
exportModellingImportance(x, outPath = ".")
# S4 method for Analysis
exportModellingImportance(x, outPath = ".")
exportModelling(x, outPath = ".")
# S4 method for Analysis
exportModelling(x, outPath = ".")
exportCorrelations(x, outPath = ".")
# S4 method for Analysis
exportCorrelations(x, outPath = ".")
exportAssignments(x, outPath = ".")
# S4 method for Assignment
exportAssignments(x, outPath = ".")
exportSummarisedAssignments(x, outPath = ".")
# S4 method for Assignment
exportSummarisedAssignments(x, outPath = ".")
exportConstruction(x, outPath = ".")
# S4 method for Construction
exportConstruction(x, outPath = ".")
exportSummarisedConstruction(x, outPath = ".")
# S4 method for Construction
exportSummarisedConstruction(x, outPath = ".")
export(x, outPath = ".", ...)
# S4 method for Binalysis
export(x, outPath = ".")
# S4 method for MetaboProfile
export(x, outPath = ".")
# S4 method for AnalysisData
export(x, outPath = ".", idx = "name", prefix = "analysis")
# S4 method for Analysis
export(x, outPath = ".", type = "raw", idx = "name")
# S4 method for Assignment
export(x, outPath = ".")
# S4 method for Construction
export(x, outPath = ".")Arguments
- x
S4 object of class
Binalysis,MetaboProfile,AnalysisorAssignment,- outPath
directory path to export to.
- ...
arguments to pass to relevant method
- idx
sample information column name to use as sample IDs
- prefix
file name prefix description
- type
data type to extract.
raworpre-treated
Examples
## Retrieve file paths and sample information for example data
files <- metaboData::filePaths('FIE-HRMS','BdistachyonEcotypes')[1:2]
info <- metaboData::runinfo('FIE-HRMS','BdistachyonEcotypes')[1:2,]
## Perform spectral binning
analysis <- binneR::binneRlyse(files,
info,
parameters = binneR::detectParameters(files))
#> binneR v2.6.3 Fri Jul 21 17:28:09 2023
#> ________________________________________________________________________________
#> Scans: 5:14
#> ________________________________________________________________________________
#> Reading raw data
#> Gathering bins
#> Removing single scan events
#> Averaging intensities across scans
#> Calculating bin metrics
#> Calculating accurate m/z
#> Building intensity matrix
#> Gathering file headers
#>
#> Completed! [2.3S]
## Export spectrally binned data
export(analysis,outPath = tempdir())
#> [1] "/tmp/RtmpDgxoTw/sample_information.csv"
#> [2] "/tmp/RtmpDgxoTw/accurate_data.csv"
#> [3] "/tmp/RtmpDgxoTw/negative_mode_processed_data.csv"
#> [4] "/tmp/RtmpDgxoTw/positive_mode_processed_data.csv"
## Perform data pre-treatment and modelling
p <- metabolyseR::analysisParameters(c('pre-treatment','modelling'))
metabolyseR::parameters(p,'pre-treatment') <- metabolyseR::preTreatmentParameters(
list(occupancyFilter = 'maximum',
transform = 'TICnorm')
)
metabolyseR::parameters(p,'modelling') <- metabolyseR::modellingParameters('anova')
metabolyseR::changeParameter(p,'cls') <- 'day'
analysis <- metabolyseR::metabolyse(metaboData::abr1$neg[,1:200],
metaboData::abr1$fact,
p)
#>
#> metabolyseR v0.15.1 Fri Jul 21 17:28:12 2023
#> ________________________________________________________________________________
#> Parameters:
#> pre-treatment
#> occupancyFilter
#> maximum
#> cls = day
#> occupancy = 2/3
#> transform
#> TICnorm
#>
#> modelling
#> anova
#> cls = day
#> pAdjust = bonferroni
#> comparisons = list()
#> returnModels = FALSE
#> ________________________________________________________________________________
#> Pre-treatment …
#>
Pre-treatment ✔ [0.6S]
#> Modelling …
#>
Modelling ✔ [0.4S]
#> ________________________________________________________________________________
#>
#> Complete! [1S]
## Export pre-treated data and modelling results
export(analysis,outPath = tempdir())
#> All objects contained within supplied list that are not of class RandomForest will be ignored.
#> [1] "/tmp/RtmpDgxoTw/raw_sample_information.csv"
#> [2] "/tmp/RtmpDgxoTw/raw_data.csv"
#> [3] "/tmp/RtmpDgxoTw/modelling_importance_metrics.csv"
## Perform molecular formula assignment
future::plan(future::sequential)
p <- assignments::assignmentParameters('FIE-HRMS')
assignments <- assignments::assignMFs(assignments::feature_data,p)
#>
#> assignments v1.0.0 Fri Jul 21 17:28:13 2023
#> ________________________________________________________________________________
#> Assignment Parameters:
#>
#> Technique: FIE-HRMS
#> Max M: 800
#> MF rank threshold: 3
#> PPM threshold: 6
#> Relationship limit: 0.001
#> RT limit:
#> Correlations:
#> method: spearman
#> pAdjustMethod: bonferroni
#> corPvalue: 0.05
#> minCoef: 0.7
#> maxCor: Inf
#>
#> Adducts:
#> n: [M-H]1-, [M+Cl]1-, [M+K-2H]1-, [M-2H]2-, [M+Cl37]1-, [2M-H]1-
#> p: [M+H]1+, [M+K]1+, [M+Na]1+, [M+K41]1+, [M+2H]2+, [2M+H]1+
#> Isotopes: 13C, 18O, 13C2
#> Transformations: M - [O] + [NH2], M - [OH] + [NH2], M + [H2], M - [H2] + [O], M - [H] + [CH3], M - [H] + [NH2], M - [H] + [OH], M + [H2O], M - [H3] + [H2O], M - [H] + [CHO2], M - [H] + [SO3], M - [H] + [PO3H2]
#> ________________________________________________________________________________
#> No. m/z: 10
#> Calculating correlations …
#> Calculating correlations ✔ [10 correlations] [0.8S]
#> Calculating relationships …
#> Calculating relationships ✔ [2.8S]
#> Adduct & isotopic assignment …
#> generating molecular formulas…
#> generating molecular formulas ✔ [24.2S]
#> iteration 1…
#> iteration 1 ✔ [0.6S]
#> iteration 2…
#> Adduct & isotopic assignment ✔ [25.6S]
#> Transformation assignment…
#> iteration 1 …
#> iteration 1 ✔ [1.5S]
#> iteration 2 …
#> Transformation assignment ✔ [1.5S]
#> ________________________________________________________________________________
#>
#> Complete! [32.9S]
## Export molecular formula assignment results
export(assignments,outPath = tempdir())
#> [1] "/tmp/RtmpDgxoTw/assignments.csv"
#> [2] "/tmp/RtmpDgxoTw/assigned_data.csv"
#> [3] "/tmp/RtmpDgxoTw/summarised_assignments.csv"
## Perform consensus structural classification
structural_classifications <- construction::construction(assignments)
#> 2 MFs to retrieve out of 2
#>
#> C6H8O7
#> Searching KEGG...
#> 14 hits returned
#> Retrieving classifications for 14 InChIKeys...
#> ✔ KRKNYBCHXYNGOX-UHFFFAOYSA-N
#> ✔ ODBLHEXUDAPZAU-UHFFFAOYSA-N
#> ✔ ODBLHEXUDAPZAU-ZAFYKAAXSA-N
#> ✔ QUURPCHWPQNNGL-ZAFYKAAXSA-N
#> ✔ RXMWXENJQAINCC-DMTCNVIQSA-N
#> ✔ CIOXZGOUEYHNBF-UHFFFAOYSA-N
#> ✔ QUURPCHWPQNNGL-OKKQSCSOSA-N
#> ✔ GJQWCDSAOUMKSE-STHAYSLISA-N
#> ✔ ODBLHEXUDAPZAU-OKKQSCSOSA-N
#> ✔ YLKFQNUGXOLRNI-KXMYSMCESA-N
#> ✔ YLKFQNUGXOLRNI-QDQPNEQZSA-N
#> ✔ XECPAIJNBXCOBO-LKELSTGYSA-N
#> ✔ QUURPCHWPQNNGL-FONMRSAGSA-N
#> ✔ XECPAIJNBXCOBO-MMPJQOAZSA-N
#> 14 classifications returned
#> Exporting to /tmp/RtmpDgxoTw
#>
#> C6H9NO7
#> Searching KEGG...
#> 0 hits returned
#> Exporting to /tmp/RtmpDgxoTw
#>
#> Complete!
## Export consensus structural classification results
export(structural_classifications,outPath = tempdir())
#> [1] "/tmp/RtmpDgxoTw/consensus_structural_classifications.csv"
#> [2] "/tmp/RtmpDgxoTw/summarised_consensus_structural_classifications.csv"