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:
FARDEEP_1.0.1.tar.gz
FARDEEP_1.0.1.zip(r-4.5)FARDEEP_1.0.1.zip(r-4.4)FARDEEP_1.0.1.zip(r-4.3)
FARDEEP_1.0.1.tgz(r-4.4-any)FARDEEP_1.0.1.tgz(r-4.3-any)
FARDEEP_1.0.1.tar.gz(r-4.5-noble)FARDEEP_1.0.1.tar.gz(r-4.4-noble)
FARDEEP_1.0.1.tgz(r-4.4-emscripten)FARDEEP_1.0.1.tgz(r-4.3-emscripten)
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:a35a92fe91. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 17 2024 |
R-4.5-win | OK | Nov 17 2024 |
R-4.5-linux | OK | Nov 17 2024 |
R-4.4-win | OK | Nov 17 2024 |
R-4.4-mac | OK | Nov 17 2024 |
R-4.3-win | OK | Nov 17 2024 |
R-4.3-mac | OK | Nov 17 2024 |
Exports:altsfardeepsample.simtuningBIC
Dependencies:nnlspreprocessCore