Package: funkycells 1.1.1.9000

Jeremy VanderDoes
funkycells: Functional Data Analysis for Multiplexed Cell Images
Compare variables of interest between (potentially large numbers of) spatial interactions and meta-variables. Spatial variables are summarized using K, or other, functions, and projected for use in a modified random forest model. The model allows comparison of functional and non-functional variables to each other and to noise, giving statistical significance to the results. Included are preparation, modeling, and interpreting tools along with example datasets, as described in VanderDoes et al., (2023) <doi:10.1101/2023.07.18.549619>.
Authors:
funkycells_1.1.1.9000.tar.gz
funkycells_1.1.1.9000.zip(r-4.7)funkycells_1.1.1.9000.zip(r-4.6)funkycells_1.1.1.9000.zip(r-4.5)
funkycells_1.1.1.9000.tgz(r-4.6-any)funkycells_1.1.1.9000.tgz(r-4.5-any)
funkycells_1.1.1.9000.tar.gz(r-4.7-any)funkycells_1.1.1.9000.tar.gz(r-4.6-any)
funkycells_1.1.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
funkycells/json (API)
| # Install 'funkycells' in R: |
| install.packages('funkycells', repos = c('https://jrvanderdoes.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jrvanderdoes/funkycells/issues
Pkgdown/docs site:https://jrvanderdoes.github.io
- TNBC - Triple Negative Breast Cancer Data
- TNBC_meta - Triple Negative Breast Cancer Phenotypes
- TNBC_pheno - Triple Negative Breast Cancer Phenotypes
Last updated from:53a257086f. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 150 | ||
| source / vignettes | OK | 249 | ||
| linux-release-x86_64 | OK | 161 | ||
| macos-release-arm64 | OK | 161 | ||
| macos-oldrel-arm64 | OK | 207 | ||
| windows-devel | OK | 131 | ||
| windows-release | OK | 106 | ||
| windows-oldrel | OK | 91 | ||
| wasm-release | OK | 105 |
Exports:computePseudoROCCurvesfunkyForestfunkyModelgetCountDatagetKFunctiongetKsPCADataplot_K_functionsplotPPpredict_funkyForestsimulateMetasimulatePP
Dependencies:abindashbitopscliclustercolorspacecpp11deldirdeSolvedplyrfarverfdafdsFNNgenericsggplot2gluegoftestgtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmgcvmulticoolmvtnormnlmepcaPPpillarpkgconfigpolyclippracmapurrrR6rainbowRColorBrewerRcppRCurlrlangrpartS7scalesspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrtensortibbletidyrtidyselectutf8vctrsviridisLitewithr
Last update: 2023-07-21
Started: 2023-07-09
Last update: 2023-07-21
Started: 2023-06-04
Last update: 2023-07-21
Started: 2023-01-04
Last update: 2023-07-18
Started: 2023-05-24
Last update: 2023-07-18
Started: 2023-07-09
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute Pseudo-ROC Curves | computePseudoROCCurves |
| Compute a Modified Random Forest Model | funkyForest |
| Fit a Modified Random Forest Model with Bounds and Alignment | funkyModel |
| Get Agent Count Data | getCountData |
| Get K function | getKFunction |
| Get K Functions and Compute Principal Components | getKsPCAData |
| Compare K Functions Between outcomes | plot_K_functions |
| Plot Spatial Point Process | plotPP |
| Predict a funkyForest | predict_funkyForest |
| Simulate Meta Variables | simulateMeta |
| Simulate a Point Process | simulatePP |
| Triple Negative Breast Cancer Data | TNBC |
| Triple Negative Breast Cancer Phenotypes | TNBC_meta |
| Triple Negative Breast Cancer Phenotypes | TNBC_pheno |