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README.md

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Algorithm

Gaussian Graphical Model-based Heterogeneity Analysis via Penalized Fusion

Maintainer

Mingyang Ren renmingyang17@mails.ucas.ac.cn

Publication

Mingyang Ren, Sanguo Zhang, Qingzhao Zhang, Shuangge Ma. (2020). Gaussian Graphical Model-based Heterogeneity Analysis via Penalized Fusion. Manuscript

Usage

The following .R files are submitted.

(Main functions for the implementation of the proposed method)

  1. function.R: This file includes all main functions of proposed methods to support numerical simulation studies and real data analysis. Detailed descriptions and manuals of these functions can be found in the notes to this R file.

(Codes for simulation studies)

  1. sim-func.R: This file includes functions for generating simulated data and evaluating performances of competitors, which are used to support numerical simulation studies. Detailed descriptions and manuals of these functions can be found in the notes to this R file.

  2. main.R: This file is used to conduct simulation studies.

(Codes for real data analysis)

  1. T_cell.R: This file is used to perform heterogeneity analysis of regulatory T cells in non-small-cell lung cancer.

  2. image_data.R: This file is used to perform LUAD heterogeneity analysis using histopathological imaging data.