Package: CalibraCurve 1.3.0

Karin Schork

CalibraCurve: Calibration curves for targeted proteomics, lipidomics and metabolomics data

CalibraCurve is a computational tool designed to generate calibration curves for targeted mass spectrometry-based quantitative data. It is applicable to various omics disciplines, including proteomics, lipidomics, and metabolomics. The package also offers functionalities for data and calibration curve visualization and concentration prediction from new datasets based on the established curves.

Authors:Karin Schork [aut, cre], Robin Grugel [aut], Michael Kohl [aut], Markus Stepath [aut], Martin Eisenacher [aut, fnd]

CalibraCurve_1.3.0.tar.gz
CalibraCurve_1.3.0.zip(r-4.7)CalibraCurve_1.3.0.zip(r-4.6)CalibraCurve_1.3.0.zip(r-4.5)
CalibraCurve_1.3.0.tgz(r-4.6-any)CalibraCurve_1.3.0.tgz(r-4.5-any)
CalibraCurve_1.3.0.tar.gz(r-4.7-any)CalibraCurve_1.3.0.tar.gz(r-4.6-any)
CalibraCurve_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
CalibraCurve/json (API)

# Install 'CalibraCurve' in R:
install.packages('CalibraCurve', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mpc-bioinformatics/calibracurve/issues

On BioConductor:CalibraCurve-1.3.0(bioc 3.24)CalibraCurve-1.2.0(bioc 3.23)

proteomicslipidomicsmetabolomicsregressionmassspectrometryvisualizationassayscalibrationdynamic-linear-rangesquantification-limitstargeted-proteomics

6.41 score 5 stars 7 scripts 13 exports 50 dependencies

Last updated from:7140fc647b. Checks:8 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE236
linux-devel-x86_64NOTE302
source / vignettesOK261
linux-release-x86_64NOTE301
macos-release-arm64NOTE148
macos-oldrel-arm64NOTE160
windows-develNOTE224
windows-releaseNOTE228
windows-oldrelNOTE202
wasm-releaseOK165

Exports:assemble_resultscalc_single_curvecalcRFcalculate_FLRcalculate_PLRCalibraCurvecleanDataplotCalibraCurveplotResponseFactorspredictConcentrationreadDataSEreadDataTablereadMultipleTables

Dependencies:abindbackportsBiobaseBiocGenericscheckmateclicpp11DelayedArraydplyrfarvergenericsGenomicRangesggplot2gluegtableIRangesisobandlabelinglatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsopenxlsxpillarpkgconfigpurrrR6RColorBrewerRcpprlangS4ArraysS4VectorsS7scalesSeqinfoSparseArraystringistringrSummarizedExperimenttibbletidyrtidyselectutf8vctrsviridisLitewithrXVectorzip

Introduction to CalibraCurve
Introduction | Installation of CalibraCurve | Asking for help | Citing CalibraCurve | Quick start to using CalibraCurve | Example data set | Import one or more xlsx, csv or txt files | Import SummarizedExperiments object | Apply CalibraCurve | Use calibration curve for prediction | Further information | Comparison with other related packages | R session information | Bibliography
Rendered fromCalibraCurve.Rmdusingknitr::rmarkdown

Last update: 2025-10-02
Started: 2025-10-02

Customizing the visualizations of CalibraCurve
Introduction | Handling multiple calibration curves | Multiplot | All-in-one plot | Changing colours | Other plot elements | R session information | Bibliography
Rendered fromCalibraCurve_Visualization.Rmdusingknitr::rmarkdown

Last update: 2025-10-02
Started: 2025-07-30

Readme and manuals

Help Manual

Help pageTopics
PLR: Calculate key features for the existing continuous preliminary ranges.calcContPrelimRanges
PLR: calculate CV for one concentration level.calcCV
FLR: calculate weighted or unweighted linear model.calcLinearModel
FLR: calculate percent bias for a specific concentration level.calcPerBias
FLR: calculate average, SD and CV percent bias for each concentration level.calcPerBiasAvgSDCV
FLR: calculate list of percent bias values for all concentration levels.calcPerBiasLevels
Calculate Response factors.calcResponseFactors
FLR: calculate weights for linear model for a specific concentration level.calcWeights
FLR: checks if final linear range has been reached (compare average percent bias with threshold).checkFinalRange
Data preprocessing: Helper function to check for sufficient number of replicates for a specific concentration level.checkNumberReplicates
Data preprocessing: Helper function to select all rows from a specific concentration level.filterConcentrationLevel
Prepare annotation data.prepareAnnotationData
Prepare calibration data.prepareCalibData
Prepare curve data.prepareCurveData
Save results of CalibraCurve.saveCCResult
Save result tables and plots.saveTablesAndPlots
FLR: selects the highest or lowest concentration level for removal.selctConcLevel
Assemble result tablesassemble_results
Calculate all necessary steps for a single calibration curvecalc_single_curve
Calculate Response factorscalcRF
Calculate the final linear rangecalculate_FLR
Calculate preliminary linear range (PLR)calculate_PLR
CalibraCurveCalibraCurve
Clean data (remove 0s and NAs, remove concentration levels with insufficient number of replicates)cleanData
Plot the calibration curveplotCalibraCurve
Plot response factorsplotResponseFactors
Predict concentrations from intensity values based on a given calibration curvepredictConcentration
Read data stored as an SummarizedExperiment object (directly or stored in an .rds file). Extracts the two relevant columns (concentration and measurement) and orders the data by increasing concentration level.readDataSE
Read data in different table input formats (xlsx, csv or txt). Extracts the two relevant columns (concentration and measurement) and orders the data by increasing concentration.readDataTable
Read folder of files in different table input formats (xlsx, csv or txt).readMultipleTables