MEM Software is provided free to academic and non-profit institutions for non-commercial research, delivering an open-source R package developed by Kirsten E. Diggins and Jonathan M. Irish at Vanderbilt University’s Meiler Lab. It quantifies marker enrichment in cell populations, enabling precise analysis for computational biology studies in immunology and cancer.
Key features include:
- Multivariate modeling to quantify feature enrichment without predefined thresholds.
- Compatibility with R environments on Windows, MacOS, and UNIX systems.
- Inclusion of source code, metadata, vignette, and sample script for flexible analysis.
- Direct access via public GitHub repository (github.com/cytolab/mem).
Benefits: MEM Software outperforms traditional methods like differential expression and clustering, streamlining cell subset characterization for publication-ready insights. Its open-source design accelerates research workflows, making it essential for academic studies in immune response and oncology.
Download the latest MEM Software files for non-commercial use at github.com/cytolab/mem. For support, visit our Contact Us page or learn more about Vanderbilt’s research at www.vanderbilt.edu/research.