Package: cytoMEM 1.9.0
Jonathan Irish
cytoMEM: Marker Enrichment Modeling (MEM)
MEM, Marker Enrichment Modeling, automatically generates and displays quantitative labels for cell populations that have been identified from single-cell data. The input for MEM is a dataset that has pre-clustered or pre-gated populations with cells in rows and features in columns. Labels convey a list of measured features and the features' levels of relative enrichment on each population. MEM can be applied to a wide variety of data types and can compare between MEM labels from flow cytometry, mass cytometry, single cell RNA-seq, and spectral flow cytometry using RMSD.
Authors:
cytoMEM_1.9.0.tar.gz
cytoMEM_1.9.0.zip(r-4.5)cytoMEM_1.9.0.zip(r-4.4)cytoMEM_1.9.0.zip(r-4.3)
cytoMEM_1.9.0.tgz(r-4.4-any)cytoMEM_1.9.0.tgz(r-4.3-any)
cytoMEM_1.9.0.tar.gz(r-4.5-noble)cytoMEM_1.9.0.tar.gz(r-4.4-noble)
cytoMEM_1.9.0.tgz(r-4.4-emscripten)cytoMEM_1.9.0.tgz(r-4.3-emscripten)
cytoMEM.pdf |cytoMEM.html✨
cytoMEM/json (API)
NEWS
| # Install 'cytoMEM' in R: |
| install.packages('cytoMEM', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cytolab/cytomem/issues
- MEM_matrix - MEM matrix
- MEM_values - MEM values
- PBMC - Normal Human Peripheral Blood Mononuclear Cells
On BioConductor:cytoMEM-1.9.0(bioc 3.20)cytoMEM-1.8.0(bioc 3.19)
Last updated 2 months agofrom:0ce41d7473
Exports:build_heatmapsMEMMEM_RMSD
Dependencies:BHBiobaseBiocGenericsbitopscaToolscpp11cytolibflowCoregplotsgtoolsKernSmoothmatrixStatsRcppRhdf5libRProtoBufLibS4Vectors
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Build heatmaps | build_heatmaps |
| Marker Enrichment Modeling | MEM |
| MEM matrix | MEM_matrix |
| MEM RMSD similarity between populations | MEM_RMSD |
| MEM values | MEM_values |
| Normal Human Peripheral Blood Mononuclear Cells (PBMCs) | PBMC |
