This repository contains the validation scripts, data pipelines, and project presentations for the cross-omics integration of transcriptomic and metabolomic time-series data. The analyses evaluate temporal correlations and lag similarities between gene expression modules and specialized plant metabolites.
The primary focus of this workspace is validating biological hypotheses through temporal correlation metrics. Recent analyses include:
- Metabolite-Gene Trajectory Mapping: Validating the temporal correlation between falcarindiol and target RNA gene clusters.
- Lag Similarity Scoring: Extracting and evaluating CF, CT, and MZ metrics across temporal datasets to confirm biosynthetic pathway hypotheses.
- Mass Spectrometry Data Filtering: High-throughput feature filtering based on strict mass-to-charge (m/z) and retention time (RT) windows to identify target lipids and eliminate early-eluting isobars.
notebook/Dual_Omics_Lag_Analysis_and_Mapping.ipynb: The primary Jupyter notebook documenting the data processing, mass/RT filtering, and temporal correlation extraction.presentation/Présentation1.zip: The project presentation detailing the analysis workflow, discussions, and biological findings.MATE_Output_cross_omics_lag_all_pairs.zip: The extracted temporal correlation datasets mapping the RNA-to-Metabolite cluster pairs.