Package: FiRE 1.0.1

FiRE: Finder of Rare Entities (FiRE)

The algorithm assigns rareness/ outlierness score to every sample in voluminous datasets. The algorithm makes multiple estimations of the proximity between a pair of samples, in low-dimensional spaces. To compute proximity, FiRE uses Sketching, a variant of locality sensitive hashing. For more details: Jindal, A., Gupta, P., Jayadeva and Sengupta, D., 2018. Discovery of rare cells from voluminous single cell expression data. Nature Communications, 9(1), p.4719. <doi:10.1038/s41467-018-07234-6>.

Authors:Prashant Gupta [aut, cre], Aashi Jindal [aut], Jayadeva [aut], Debarka Sengupta [aut]

FiRE_1.0.1.tar.gz
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FiRE.pdf |FiRE.html✨
FiRE/json (API)

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

Peer review:

Bug tracker:https://github.com/princethewinner/fire/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • sample_data - Preprocessed 293T–Jurkat scRNA-seq dataset
  • sample_label - Labels of preprocessed 293T–Jurkat scRNA-seq dataset

On CRAN:

1 exports 0.71 score 2 dependencies 2 mentions 7 scripts 213 downloads

Last updated 3 years agofrom:56eaca7551. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-win-x86_64OKSep 07 2024
R-4.5-linux-x86_64OKSep 07 2024
R-4.4-win-x86_64OKSep 07 2024
R-4.4-mac-x86_64OKSep 07 2024
R-4.4-mac-aarch64OKSep 07 2024
R-4.3-win-x86_64OKSep 07 2024
R-4.3-mac-x86_64OKSep 07 2024
R-4.3-mac-aarch64OKSep 07 2024

Exports:FiRE

Dependencies:BHRcpp