afeblir

Afeblir is a data‑analysis platform that specializes in the integration of heterogeneous biological datasets for the purpose of identifying novel genetic markers. The software was first released by the laboratory of Dr. Elena Morozova at the Institute of Systems Biology in 2017. It was developed to address limitations in existing pipelines, particularly the difficulty of reconciling differences in data resolution, annotation standards, and experimental conditions across large-scale genomics, proteomics, and metabolomics studies.

The core functionality of Afeblir relies on a modular architecture. The input module facilitates the ingestion of raw sequence files, transcriptomic counts, and metabolite abundance tables. A central normalization engine applies variance‑stabilizing transformations, batch‑effect correction, and cross‑platform mapping. The analysis module employs unsupervised clustering, supervised machine learning, and network reconstruction to detect correlated biological signals. Results can be visualized through interactive dashboards that display heatmaps, correlation networks, and multidimensional scaling plots. All analyses are fully reproducible: each workflow is logged in a versioned metadata repository and can be exported as a command‑line script for command‑line usage.

Since its release, Afeblir has been cited in over twenty peer‑reviewed publications. It is widely used in pharmacogenomics research, particularly for the identification of drug‑response biomarkers. The platform is distributed under the MIT license and is available on GitHub, supporting Windows, macOS, and Linux operating systems. Active development continues, with planned improvements to support single‑cell sequencing data and integration with cloud‑based high‑performance computing resources.