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>.
| Version: |
1.0.1 |
| Depends: |
R (≥ 3.3.0) |
| Imports: |
nnls (≥ 1.4), stats, preprocessCore |
| Published: |
2019-04-24 |
| DOI: |
10.32614/CRAN.package.FARDEEP |
| Author: |
Yuning Hao [aut],
Ming Yan [aut],
Blake R. Heath [aut],
Yu L. Lei [aut],
Yuying Xie [aut, cre] |
| Maintainer: |
Yuying Xie <xyy at egr.msu.edu> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| CRAN checks: |
FARDEEP results |
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