Package: cytoKernel 1.13.0

Tusharkanti Ghosh

cytoKernel: Differential expression using kernel-based score test

cytoKernel implements a kernel-based score test to identify differentially expressed features in high-dimensional biological experiments. This approach can be applied across many different high-dimensional biological data including gene expression data and dimensionally reduced cytometry-based marker expression data. In this R package, we implement functions that compute the feature-wise p values and their corresponding adjusted p values. Additionally, it also computes the feature-wise shrunk effect sizes and their corresponding shrunken effect size. Further, it calculates the percent of differentially expressed features and plots user-friendly heatmap of the top differentially expressed features on the rows and samples on the columns.

Authors:Tusharkanti Ghosh [aut, cre], Victor Lui [aut], Pratyaydipta Rudra [aut], Souvik Seal [aut], Thao Vu [aut], Elena Hsieh [aut], Debashis Ghosh [aut, cph]

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cytoKernel.pdf |cytoKernel.html
cytoKernel/json (API)
NEWS

# Install 'cytoKernel' in R:
install.packages('cytoKernel', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ghoshlab/cytokernel/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • cytoHDBMW - Example of processed dimensionally reduced flow cytometry (marker median intensities) Bodenmiller_BCR_XL_flowSet() expression dataset from HDCytoData Bioconductor data package.

On BioConductor:cytoKernel-1.13.0(bioc 3.21)cytoKernel-1.12.0(bioc 3.20)

immunooncologyproteomicssinglecellsoftwareonechannelflowcytometrydifferentialexpressiongeneexpressionclusteringcpp

4.00 score 4 scripts 156 downloads 10 exports 77 dependencies

Last updated 2 months agofrom:ee6062c066. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 18 2024
R-4.5-win-x86_64OKDec 18 2024
R-4.5-linux-x86_64OKDec 18 2024
R-4.4-win-x86_64OKDec 18 2024
R-4.4-mac-x86_64OKDec 18 2024
R-4.4-mac-aarch64OKDec 18 2024
R-4.3-win-x86_64OKDec 18 2024
R-4.3-mac-x86_64OKDec 18 2024
R-4.3-mac-aarch64OKDec 18 2024

Exports:CytoKCytoKalphaCytoKDataCytoKDEDataCytoKDEfeaturesCytoKFeaturesCytoKFeaturesOrderedCytoKFeatureVarsCytoKProcplotCytoK

Dependencies:abindashraskpassBHBiobaseBiocGenericsBiocParallelcirclizecliclueclustercodetoolscolorspaceComplexHeatmapcpp11crayoncurldata.tableDelayedArraydigestdoParalleldplyretrunctfansiforeachformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGetoptLongGlobalOptionsgluehttrinvgammaIRangesirlbaiteratorsjsonlitelambda.rlatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmimemixsqpopensslpillarpkgconfigpngR6RColorBrewerRcppRcppArmadillorjsonrlangS4ArraysS4VectorsshapesnowSparseArraySQUAREMSummarizedExperimentsystibbletidyselecttruncnormUCSC.utilsutf8vctrswithrXVectorzlibbioc

The cytoKernel user's guide

Rendered fromcytoKernel.Rmdusingknitr::rmarkdownon Dec 18 2024.

Last update: 2021-10-01
Started: 2021-10-01