Package: microSTASIS 1.5.0
microSTASIS: Microbiota STability ASsessment via Iterative cluStering
The toolkit 'µSTASIS', or microSTASIS, has been developed for the stability analysis of microbiota in a temporal framework by leveraging on iterative clustering. Concretely, the core function uses Hartigan-Wong k-means algorithm as many times as possible for stressing out paired samples from the same individuals to test if they remain together for multiple numbers of clusters over a whole data set of individuals. Moreover, the package includes multiple functions to subset samples from paired times, validate the results or visualize the output.
Authors:
microSTASIS_1.5.0.tar.gz
microSTASIS_1.5.0.zip(r-4.5)microSTASIS_1.5.0.zip(r-4.4)microSTASIS_1.5.0.zip(r-4.3)
microSTASIS_1.5.0.tgz(r-4.4-any)microSTASIS_1.5.0.tgz(r-4.3-any)
microSTASIS_1.5.0.tar.gz(r-4.5-noble)microSTASIS_1.5.0.tar.gz(r-4.4-noble)
microSTASIS_1.5.0.tgz(r-4.4-emscripten)microSTASIS_1.5.0.tgz(r-4.3-emscripten)
microSTASIS.pdf |microSTASIS.html✨
microSTASIS/json (API)
NEWS
# Install 'microSTASIS' in R: |
install.packages('microSTASIS', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/biotechpedro/microstasis/issues
- clr - Detected ASV from multiple individuals at four different sampling times.
On BioConductor:microSTASIS-1.5.0(bioc 3.20)microSTASIS-1.4.0(bioc 3.19)
Last updated 2 months agofrom:00fe97a14b
Exports:iterativeClusteringiterativeClusteringCVmSerrorCVmSinternalPairedTimesmSmetadataGroupsmSprevizpairedTimesplotmSdynamicsplotmSheatmapplotmSlinesCVplotmSscatter
Dependencies:abindapeaskpassBHBiobaseBiocGenericsBiocParallelBiostringscachemclicodetoolscolorspacecpp11crayoncurlDelayedArraydigestdplyrfansifarverfastmapformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggsidegluegtablehttrIRangesisobandjsonlitelabelinglambda.rlatticelazyevallifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigpurrrR6RColorBrewerRcpprlangS4ArraysS4VectorsscalesSingleCellExperimentsnowSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttidytreetreeioTreeSummarizedExperimentUCSC.utilsutf8vctrsviridisLitewithrXVectoryulab.utilszlibbioc