Package: diffcyt 1.27.0
diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering
Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.
Authors:
diffcyt_1.27.0.tar.gz
diffcyt_1.27.0.zip(r-4.5)diffcyt_1.27.0.zip(r-4.4)diffcyt_1.27.0.zip(r-4.3)
diffcyt_1.25.0.tgz(r-4.4-any)diffcyt_1.25.0.tgz(r-4.3-any)
diffcyt_1.27.0.tar.gz(r-4.5-noble)diffcyt_1.27.0.tar.gz(r-4.4-noble)
diffcyt_1.27.0.tgz(r-4.4-emscripten)diffcyt_1.27.0.tgz(r-4.3-emscripten)
diffcyt.pdf |diffcyt.html✨
diffcyt/json (API)
NEWS
# Install 'diffcyt' in R: |
install.packages('diffcyt', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lmweber/diffcyt/issues
On BioConductor:diffcyt-1.25.0(bioc 3.20)diffcyt-1.24.0(bioc 3.19)
immunooncologyflowcytometryproteomicssinglecellcellbasedassayscellbiologyclusteringfeatureextractionsoftware
Last updated 25 days agofrom:c9fca526be. Checks:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | NOTE | Oct 30 2024 |
R-4.5-linux | NOTE | Oct 30 2024 |
R-4.4-win | NOTE | Oct 30 2024 |
R-4.4-mac | NOTE | Oct 10 2024 |
R-4.3-win | NOTE | Oct 30 2024 |
R-4.3-mac | NOTE | Oct 10 2024 |
Exports:calcCountscalcMedianscalcMediansByClusterMarkercalcMediansBySampleMarkercreateContrastcreateDesignMatrixcreateFormuladiffcytgenerateClustersplotHeatmapprepareDatatestDA_edgeRtestDA_GLMMtestDA_voomtestDS_limmatestDS_LMMtopClusterstopTabletransformData
Dependencies:abindALLaskpassbackportsBHBiobaseBiocGenericsbootbroomcarcarDatacirclizecliclueclustercodetoolscolorRampscolorspaceComplexHeatmapConsensusClusterPluscorrplotcowplotcpp11crayoncurlcytolibDelayedArrayDerivdigestdoBydoParalleldplyredgeRfansifarverflowCoreFlowSOMforeachFormulagenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGetoptLongggforceggnewscaleggplot2ggpubrggrepelggsciggsignifGlobalOptionsgluegridExtragtablehttrigraphIRangesisobanditeratorsjsonlitelabelinglatticelifecyclelimmalme4locfitmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmgcvmicrobenchmarkmimeminqamodelrmultcompmunsellmvtnormnlmenloptrnnetnumDerivopensslpbkrtestpillarpkgconfigplyrpngpolyclippolynompurrrquantregR6RColorBrewerRcppRcppEigenreshape2Rhdf5librjsonrlangRProtoBufLibrstatixRtsneS4ArraysS4VectorssandwichscalesshapeSparseArraySparseMstatmodstringistringrSummarizedExperimentsurvivalsyssystemfontsTH.datatibbletidyrtidyselecttweenrUCSC.utilsutf8vctrsviridisLitewithrXMLXVectorzlibbioczoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Calculate cluster cell counts | calcCounts |
Calculate cluster medians | calcMedians |
Calculate medians (by cluster and marker) | calcMediansByClusterMarker |
Calculate medians (by sample and marker) | calcMediansBySampleMarker |
Create contrast matrix | createContrast |
Create design matrix | createDesignMatrix |
Create model formula and corresponding data frame of variables | createFormula |
Run 'diffcyt' pipeline | diffcyt-package diffcyt |
Generate clusters | generateClusters |
Plot heatmap | plotHeatmap |
Prepare data | prepareData |
Test for differential abundance: method 'diffcyt-DA-edgeR' | testDA_edgeR |
Test for differential abundance: method 'diffcyt-DA-GLMM' | testDA_GLMM |
Test for differential abundance: method 'diffcyt-DA-voom' | testDA_voom |
Test for differential states: method 'diffcyt-DS-limma' | testDS_limma |
Test for differential states: method 'diffcyt-DS-LMM' | testDS_LMM |
Alias for 'topTable' (deprecated) | topClusters |
Show table of results for top clusters or cluster-marker combinations | topTable |
Transform data | transformData |