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'))

Peer review:

Datasets:
  • LM22 - Siganature matrix
  • mixture - Gene-expression data from 14 follicular lymphoma patients

On CRAN:

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

2.35 score 45 scripts 221 downloads 5 mentions 4 exports 2 dependencies

Last updated 6 years agofrom:a35a92fe91. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

Exports:altsfardeepsample.simtuningBIC

Dependencies:nnlspreprocessCore