Package: adSplit 1.77.0
adSplit: Annotation-Driven Clustering
This package implements clustering of microarray gene expression profiles according to functional annotations. For each term genes are annotated to, splits into two subclasses are computed and a significance of the supporting gene set is determined.
Authors:
adSplit_1.77.0.tar.gz
adSplit_1.77.0.zip(r-4.5)adSplit_1.77.0.zip(r-4.4)adSplit_1.77.0.zip(r-4.3)
adSplit_1.77.0.tgz(r-4.4-x86_64)adSplit_1.77.0.tgz(r-4.4-arm64)adSplit_1.77.0.tgz(r-4.3-x86_64)adSplit_1.77.0.tgz(r-4.3-arm64)
adSplit_1.77.0.tar.gz(r-4.5-noble)adSplit_1.77.0.tar.gz(r-4.4-noble)
adSplit_1.77.0.tgz(r-4.4-emscripten)adSplit_1.77.0.tgz(r-4.3-emscripten)
adSplit.pdf |adSplit.html✨
adSplit/json (API)
# Install 'adSplit' in R: |
install.packages('adSplit', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- golubKEGGSplits - Examplar splitSet
On BioConductor:adSplit-1.77.0(bioc 3.21)adSplit-1.76.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:7c97ce73a7. Checks:OK: 5 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 29 2024 |
R-4.5-win-x86_64 | OK | Nov 29 2024 |
R-4.5-linux-x86_64 | OK | Nov 29 2024 |
R-4.4-win-x86_64 | OK | Nov 29 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 29 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 29 2024 |
R-4.3-win-x86_64 | OK | Nov 29 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 29 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 29 2024 |
Exports:adSplitdiana2meansdrawRandomPSmakeEID2PROBESenvrandomDiana2means
Dependencies:AnnotationDbiaskpassBiobaseBiocGenericsBiostringsbitbit64blobcachemcliclustercpp11crayoncurlDBIfastmapgenericsGenomeInfoDbGenomeInfoDbDataglueGO.dbhttrIRangesjsonliteKEGGRESTlatticelifecycleMASSMatrixmemoisemimemulttestopensslpkgconfigplogrpngR6rlangRSQLiteS4VectorssurvivalsysUCSC.utilsvctrsXVectorzlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Annotation-Driven Splits | adSplit |
2-Means with Hierarchical Initialization | diana2means |
Draw sets of probe-sets | drawRandomPS |
Examplar splitSet | golubKEGGSplits |
Overview Histogram for splitSets | hist,splitSet-method hist.splitSet |
Illustrate Split Sets | image,splitSet-method image.splitSet |
Generate EID2PROBES environment | makeEID2PROBESenv |
Generate null-distributions of DLD-scores | randomDiana2means |