This repository contains the source code and data of all programs used in the manuscript "Exploring the use of deep learning to assess immune infiltration in patients with hepatocellular carcinoma".
The raw data of R scripts are stored in the /R/Data directory, and the deep learning training data used by C# programs are available on the release page. In addition, the tile data of the Xijing Hospital cohort used for validation is stored in the RELEASE page.
DL-in-HCC
├── C# C# related projects
│ ├── DL-in-HCC.sln Solution file
│ ├── Tile Classifier Function as folder name
│ └── Wistu.Lib.ClassifyModel Public library, 'wistu' is the author's blog name
├── LICENSE
├── R R related scripts
│ ├── 00.Functions.R Basic functions of the script
│ ├── 01.CalculateCutoff.R The name is its function
│ ├── 02.DrawOS.R The name is its function
│ ├── 03.CoxRegression.R The name is its function
│ ├── 04.Nomogram.R The name is its function
│ ├── 05.CalibrationCurve.R The name is its function
│ ├── 06.Time-dependentROCCurve.R The name is its function
│ ├── 07.CIBERSORT.R The name is its function
│ ├── 08.EnrichmentAnalysis.R The name is its function
│ ├── 09.ImmuneCheckpointExpression.R The name is its function
│ ├── Data Contains the data needed for the script
│ └── R.Rproj R project file
└── README.md
The main role of this tool is to assist users in fast and efficient tile classification, while it can use already trained models to assist in classification.
Use keyboard shortcuts to sort the tiles. For more details, please refer to the source code.
The R scripts have been split into separate units according to their functions, and each R script runs interdependently but independently of each other. Note: If you cannot output the image by executing the corresponding R script directly, please press Ctrl+Enter in R studio to run the code line by line and get the image in the Plot window.
Python项目主要用于模型的训练以及评估。