Package: FateID 0.2.2

FateID: Quantification of Fate Bias in Multipotent Progenitors

Application of 'FateID' allows computation and visualization of cell fate bias for multi-lineage single cell transcriptome data. Herman, J.S., Sagar, Grün D. (2018) <doi:10.1038/nmeth.4662>.

Authors:Dominic Grün <[email protected]>

FateID_0.2.2.tar.gz
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FateID.pdf |FateID.html✨
FateID/json (API)

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

Peer review:

Bug tracker:https://github.com/dgrun/fateid/issues

Datasets:
  • intestine - Single-cell transcriptome data of intestinal epithelial cells

On CRAN:

6.49 score 22 stars 1 packages 47 scripts 310 downloads 2 mentions 17 exports 37 dependencies

Last updated 2 years agofrom:f2ea6f9b49. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winOKNov 02 2024
R-4.5-linuxOKNov 02 2024
R-4.4-winOKNov 02 2024
R-4.4-macOKNov 02 2024
R-4.3-winOKNov 02 2024
R-4.3-macOKNov 02 2024

Exports:compdrdiffexpnbfateBiasfiltersetgene2genegetFeatgetPartgetsomimpGenesplotdiffgenesnbplotexpressionplotexpressionProfileplotFateMapplotheatmapprcurveprocsomreclassify

Dependencies:askpassclicolorspacefarvergluegtableherejsonlitelabelinglatticelifecyclelocfitMatrixmatrixStatsmunsellopensslpheatmappngprincurveR6randomForestrappdirsRColorBrewerRcppRcppEigenRcppTOMLreticulaterlangrprojrootRSpectraRtsnescalessomsysumapviridisLitewithr

FateID reference manual

Rendered fromFateID.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2022-06-14
Started: 2017-11-07