Package: CytoDx 1.25.0
Zicheng Hu
CytoDx: Robust prediction of clinical outcomes using cytometry data without cell gating
This package provides functions that predict clinical outcomes using single cell data (such as flow cytometry data, RNA single cell sequencing data) without the requirement of cell gating or clustering.
Authors:
CytoDx_1.25.0.tar.gz
CytoDx_1.25.0.zip(r-4.5)CytoDx_1.25.0.zip(r-4.4)CytoDx_1.25.0.zip(r-4.3)
CytoDx_1.25.0.tgz(r-4.4-any)CytoDx_1.25.0.tgz(r-4.3-any)
CytoDx_1.25.0.tar.gz(r-4.5-noble)CytoDx_1.25.0.tar.gz(r-4.4-noble)
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CytoDx.pdf |CytoDx.html✨
CytoDx/json (API)
NEWS
| # Install 'CytoDx' in R: |
| install.packages('CytoDx', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:CytoDx-1.25.0(bioc 3.20)CytoDx-1.24.0(bioc 3.19)
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:35e0c5cf86
Exports:CytoDx.fitCytoDx.predfcs2DFmeanUniquepRankrank.ub.averageset2DFtreeGate
Dependencies:BHBiobaseBiocGenericsclicodetoolscpp11cytolibdoParalleldplyrfansiflowCoreforeachgenericsglmnetglueiteratorslatticelifecyclemagrittrMatrixmatrixStatspillarpkgconfigR6RcppRcppEigenRhdf5librlangrpartrpart.plotRProtoBufLibS4Vectorsshapesurvivaltibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Build the CytoDx model | CytoDx.fit |
| Make prediction using the CytoDx model | CytoDx.pred |
| Convert fcs files to a data frame | fcs2DF |
| Calulate mean or take unique elements of a vector | meanUnique |
| Percentile rank transformation of the data | pRank |
| Percentile rank transformation of a vector | rank.ub.average |
| convert a flowSet to a data frame | set2DF |
| Use decision tree to find a group of cells that are associated with clinical outcome. | treeGate |