Intro to Marker Enrichment Modeling | Installing MEM | Example Data: Normal Human Peripheral Blood Cells (PBMC) | Input data: File format and structure | Multiple Files | Reading files in to R | Use of file.is.clust and add.fileID | Data Format | Arcsinh Transformation | Reference Population Selection | IQR Thresholding | Putting it all together: MEM analysis of PBMC | Column names in your file will be printed to the console | Generating MEM labels and heatmaps | Arguments of build_heatmaps() | Generating RMSD (similarity) scores
Package: cytoMEM 1.17.0
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_1.17.0.tar.gz
cytoMEM_1.17.0.zip(r-4.7)cytoMEM_1.17.0.zip(r-4.6)cytoMEM_1.17.0.zip(r-4.5)
cytoMEM_1.17.0.tgz(r-4.6-any)cytoMEM_1.17.0.tgz(r-4.5-any)
cytoMEM_1.17.0.tar.gz(r-4.7-any)cytoMEM_1.17.0.tar.gz(r-4.6-any)
cytoMEM_1.17.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cytoMEM/json (API)
| # 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
Datasets:
- MEM_matrix - MEM matrix
- MEM_values - MEM values
- PBMC - Normal Human Peripheral Blood Mononuclear Cells
On BioConductor:cytoMEM-1.17.0(bioc 3.24)cytoMEM-1.16.0(bioc 3.23)
proteomicssystemsbiologyclassificationflowcytometrydatarepresentationdataimportcellbiologysinglecellclustering
Last updated from:e684e94048. Checks:8 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 164 | ||
| linux-devel-x86_64 | NOTE | 180 | ||
| source / vignettes | OK | 256 | ||
| linux-release-x86_64 | NOTE | 186 | ||
| macos-release-arm64 | NOTE | 139 | ||
| macos-oldrel-arm64 | NOTE | 94 | ||
| windows-devel | NOTE | 112 | ||
| windows-release | NOTE | 107 | ||
| windows-oldrel | NOTE | 108 | ||
| wasm-release | OK | 156 |
Exports:build_heatmapsMEMMEM_RMSD
Dependencies:BHBiobaseBiocGenericsbiocmakebitopscaToolscpp11cytolibdir.expiryfilelockflowCoregenericsgplotsgtoolsKernSmoothmatrixStatsRcppRhdf5libRProtoBufLibS4Vectors
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 |
