MEM Release Notes provide a detailed log of updates and enhancements for Marker Enrichment Modeling, an open-source R package developed by Kirsten E. Diggins and Jonathan M. Irish at Vanderbilt University’s Meiler Lab. Designed to quantify marker enrichment in cell populations for computational biology research, MEM supports discoveries in immunology and cancer. The notes below outline version changes, feature improvements, and fixes to ensure efficient, reliable analysis for your studies. For support, visit our Contact Us page, explore licensing options on the licensing page, or learn more about Vanderbilt’s research at www.vanderbilt.edu/research.
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11 Jul 2019
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Public Github repository released: https://github.com/cytolab/mem Please download the most recently updated files from Github.
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30 Mar 2018
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- The MEM() function now includes the option "output_prescaled_MEM" that, when set to TRUE, outputs a TXT file containing pre-scaled MEM scores.
- When MAGpop = MAGref and IQRpop < IQRref, the MEM score will always be negative. This prevents positive MEM scores on populations that do not express a given marker.
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12 Sep 2017
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- Build.heatmaps function outputs IQR heatmap and text file
- Added a new function, MEM_RMSD, that compares populations given their MEM scores.
- Updated MEM algorithm to prevent erroneously negative MEM scores when MAGpop-MAGref is near zero and IQRref < IQRpop.
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19 Jun 2017
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- Updated code to fix the file output error when running build.heatmaps() function.
- A detailed R script for installing and running MEM
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10 Apr 2017
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- Added a sample R script that guides the user through the installation and analysis process.
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6 Mar 2017
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- Initial Build