Package: FARDEEP 1.0.1

FARDEEP: Fast and Robust Deconvolution of Tumor Infiltrating Lymphocyte from Expression Profiles using Least Trimmed Squares

Using the idea of least trimmed square, it could automatically detects and removes outliers from data before estimating the coefficients. It is a robust machine learning tool which can be applied to gene-expression deconvolution technique. Yuning Hao, Ming Yan, Blake R. Heath, Yu L. Lei and Yuying Xie (2019) <doi:10.1101/358366>.

Authors:Yuning Hao [aut], Ming Yan [aut], Blake R. Heath [aut], Yu L. Lei [aut], Yuying Xie [aut, cre]

FARDEEP_1.0.1.tar.gz
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FARDEEP.pdf |FARDEEP.html
FARDEEP/json (API)

# Install 'FARDEEP' in R:
install.packages('FARDEEP', repos = c('https://yuyingxie.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • LM22 - Siganature matrix
  • mixture - Gene-expression data from 14 follicular lymphoma patients

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.39 score 49 scripts 249 downloads 5 mentions 4 exports 2 dependencies

Last updated 6 years agofrom:a35a92fe91. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-winOKMar 17 2025
R-4.5-macOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-winOKMar 17 2025
R-4.4-macOKMar 17 2025
R-4.4-linuxOKMar 17 2025
R-4.3-winOKMar 17 2025
R-4.3-macOKMar 17 2025

Exports:altsfardeepsample.simtuningBIC

Dependencies:nnlspreprocessCore