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FARDEEP (version 1.0.1)

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

Description

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) .

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Version

Install

install.packages('FARDEEP')

Monthly Downloads

247

Version

1.0.1

License

MIT + file LICENSE

Maintainer

Yuying Xie

Last Published

April 24th, 2019

Functions in FARDEEP (1.0.1)

fardeep

Using the idea of least trimmed square to detect and remove outliers before estimating the coefficients. A robust method for gene-expression deconvolution.
LM22

Siganature matrix
alts

Using the basic idea of least trimmed square to detect and remove outliers before estimating the coefficients. Adaptive least trimmed square.
sample.sim

Generate random sample with different proportion of outliers and leverage points
tuningBIC

Tuning parameter k in function alts using Bayesian Information Criterion (BIC) with some adjustment.
mixture

Gene-expression data from 14 follicular lymphoma patients