Automated analysis and modeling of longitudinal 'omics' data (e.g. breath 'metabolomics') using generalized spline mixed effect models. Including automated filtering of noise parameters and determination of breakpoints.
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.