Package: mxfda 0.2.2
Alex Soupir
mxfda: A Functional Data Analysis Package for Spatial Single Cell Data
Methods and tools for deriving spatial summary functions from single-cell imaging data and performing functional data analyses. Functions can be applied to other single-cell technologies such as spatial transcriptomics. Functional regression and functional principal component analysis methods are in the 'refund' package <https://cran.r-project.org/package=refund> while calculation of the spatial summary functions are from the 'spatstat' package <https://spatstat.org/>.
Authors:
mxfda_0.2.2.tar.gz
mxfda_0.2.2.zip(r-4.5)mxfda_0.2.2.zip(r-4.4)mxfda_0.2.2.zip(r-4.3)
mxfda_0.2.2.tgz(r-4.4-any)mxfda_0.2.2.tgz(r-4.3-any)
mxfda_0.2.2.tar.gz(r-4.5-noble)mxfda_0.2.2.tar.gz(r-4.4-noble)
mxfda_0.2.2.tgz(r-4.4-emscripten)mxfda_0.2.2.tgz(r-4.3-emscripten)
mxfda.pdf |mxfda.html✨
mxfda/json (API)
| # Install 'mxfda' in R: |
| install.packages('mxfda', repos = c('https://julia-wrobel.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/julia-wrobel/mxfda/issues
- lung_FDA - Multiplex imaging data from a non-small cell lung cancer study
- lung_df - Multiplex imaging data from a non-small cell lung cancer study.
- ovarian_FDA - Multiplex imaging data from an ovarian cancer tumor microarray
Last updated 1 months agofrom:02bd0c2405. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 13 2024 |
| R-4.5-win | OK | Nov 13 2024 |
| R-4.5-linux | OK | Nov 13 2024 |
| R-4.4-win | OK | Nov 13 2024 |
| R-4.4-mac | OK | Nov 13 2024 |
| R-4.3-win | OK | Nov 13 2024 |
| R-4.3-mac | OK | Nov 13 2024 |
Exports:%>%add_summary_functionbivariatecan_permuteentropyextract_cextract_entropyextract_fpca_objectextract_fpca_scoresextract_modelextract_spatial_summaryextract_summary_functionsextract_surfacefilter_datafilter_spatialGcrossGestget_datais.emptyKcrossKestLcrossLestmake_mxfdametric.existsone_zeroplot_fpcplot_mfpcrun_fcmrun_fpcarun_mfcmrun_mfpcarun_sofrspatialTIME_summary_functionsunivariate
Dependencies:abindashaudiobeeprbitopsbootbriocallrcliclustercodetoolscolorspacecpp11crayoncurldeldirdescdeSolvediffobjdigestdplyrevaluatefansifarverfdafdsFNNfsfuturefuture.applygamm4genericsggplot2globalsgluegoftestgrpreggtablehdrcdeisobandjsonlitekernlabKernSmoothkslabelinglatticelifecyclelistenvlme4locfitmagicmagrittrMASSMatrixmclustmgcvminqamulticoolmunsellmvtnormnlmenloptrparallellypbapplypbspcaPPpillarpkgbuildpkgconfigpkgloadplyrpolyclippracmapraiseprocessxprogressrpspurrrR.methodsS3R.ooR.utilsR6rainbowRColorBrewerRcppRcppEigenRCurlrefundreshape2rlangRLRsimrpartrprojrootRPushbulletscalessessioninfoSimDesignsnowSpatEntropyspatstatspatstat.dataspatstat.explorespatstat.geomspatstat.linnetspatstat.modelspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrtensortestthattibbletidyrtidyselectutf8vctrsviridisLitewaldowithr
Defining an mxFDA object
Rendered frommx_fda.Rmdusingknitr::rmarkdownon Nov 13 2024.Last update: 2024-10-04
Started: 2023-05-16
Functional principal component analysis for spatial summary functions
Rendered frommx_fpca.Rmdusingknitr::rmarkdownon Nov 13 2024.Last update: 2024-10-04
Started: 2023-11-16
Functional regression with spatial summary functions as covariates
Rendered frommx_funreg.Rmdusingknitr::rmarkdownon Nov 13 2024.Last update: 2024-10-04
Started: 2023-05-16
