Package: tidydr 0.0.5.001

Guangchuang Yu

tidydr: Unify Dimensionality Reduction Results

Dimensionality reduction (DR) is widely used in many domain for analyzing and visualizing high-dimensional data. 'tidydr' provides uniform output and is compatible with multiple methods, including 'prcomp', 'mds', 'Rtsne'. etc.

Authors:Guangchuang Yu [aut, cre, cph], Shuangbin Xu [aut], Erqiang Hu [ctb]

tidydr_0.0.5.001.tar.gz
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tidydr.pdf |tidydr.html
tidydr/json (API)
NEWS

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

Bug tracker:https://github.com/yulab-smu/tidydr/issues

On CRAN:

Conda:

6.47 score 14 stars 1 packages 71 scripts 899 downloads 9 exports 36 dependencies

Last updated 1 years agofrom:344e23531d. Checks:1 ERROR, 7 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesFAILMar 01 2025
R-4.5-winOKMar 01 2025
R-4.5-macOKMar 01 2025
R-4.5-linuxOKMar 01 2025
R-4.4-winOKMar 01 2025
R-4.4-macOKMar 01 2025
R-4.3-winOKMar 01 2025
R-4.3-macOKMar 01 2025

Exports:aesautoplotavailable_methodsdrdr_extractelement_line2nktheme_drtheme_noaxis

Dependencies:cliclustercolorspacedigestdplyrfansifarverfsgenericsggfunggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbletidyselectutf8vctrsviridisLitewithryulab.utils

Unify Dimensionality Reduction Results

Rendered fromtidydr.Rmdusingknitr::rmarkdownon Mar 01 2025.

Last update: 2022-03-16
Started: 2021-12-07