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LoBrA

R package for modeling of longitudinal breath data (Longitudinal Breath Analysis). Novel metabolomics technologies paved the way for longitudinal analysis of exhaled air and online monitoring of fast progressing diseases. This package implements an analysis approach of longitudinal data from technologies, such as ion mobility spectrometry of human exhaled air and demonstrates how including temporal signals increases the statistical power in biomarker identification.

This package was developed in collaboration with the Division of Biostatistics at University of Southern California, the department of Experimental Bioinformatics at Technical University of Munich and the International Max Planck Research School. It is subject to the GNU General Public License, https://www.gnu.org/licenses/licenses.en.html.

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Version

Install

install.packages('LoBrA')

Monthly Downloads

180

Version

1.0

License

GPL-3

Maintainer

Anne-Christin Hauschild

Last Published

March 21st, 2022

Functions in LoBrA (1.0)

lobraModelSelection

Evaluation of different spline variants.

plotmodelSelectionEvaluation

Plotting results of Model Evaluation and Selection.

'LoBrA' Data Object (LDO) for Example data set

Testing differences of groups with respect to a specific value and test.

Plotting function for a longitudinal data matrix (Internal Function)

createExampleData

Create example data set for 'LoBrA'

modelGoudermanLongitudinal

Fitting the Gouderman LME Model with using Gouderman-Data Arrangement.

createGoudermanData

Create the Gouderman Data Arrangement.

plotGaudermanModel

Plotting helper function to plot a single generalized gouderman Model

getGeneralizedGaudermanDataFrame

Create Peak Matrices for Generalized 'Gauderman' linear mixed effect regression (LMER) Model with parameterized Times

getOptimalSpline

Extract the optimal spline model parameters from the ModelSelection Object.

longDataExample

'LoBrA' Example Data Set

plotGoudermanLongitudinalResults

Plotting the 'Gouderman' LME Model and Results.

Creating the power set of a set.

Screening of background or confounding components

LDOmodelselection-class

An S4 class to represent a model selection result based on an 'LDO'.

Get colors for the plotting function.

createInformativeComponents

Simulate informative peaks

selectComponents

Create a new 'LDO' Object that only contains the selected components.

plotLDOScreening

Plotting the screening results.

GaudermanModelEvaluation-class

An S4 class to represent the result of the linear mixed effect modeling on a gauderman LDO.

LDOscreening-class

An S4 class to represent the screening of metabolites in an 'LDO'.

Transformation of a single longitudinal data matrix into 'LoBrA' Data Object.

createBGComponents

Simulate background noise peaks

GaudermanLDO-class

An S4 class to represent a 'Gouderman' LDO object, that was generated by the generalized gauderman algorithm.

An S4 class to represent a 'LoBrA' Data Object (LDO). It stores multiple time series data for muliple experiements and multiple Components. It allows repeated measurements of a component, irregular sampling, and unequal temporal spacing of the time points.

'LoBrA' Data Object (LDO) for Example data set

LoBrA: A package for modeling longitudinal breath data

Simulate background measurements