This repository contains the StiffCalc model, which predicts tumor matrix stiffness based on aligned RNA-seq read counts.
StiffCalc determines tumor rigidity (stiff or soft) by processing RNA-seq data. This tool is optimized for large-scale tumor studies and outputs categorical stiffness predictions for each sample.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
- This package is supported for Linux operating systems. The package has been tested on the following systems:
Linux: Ubuntu 18.04.4 LTS
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R version 4.3.2 is required.
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Conda is required.
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R packages required in StiffCalc.
- glmnet
- optparse
To obtain StiffCalc, clone the repository from GitHub:
- Download StiffCalc from GitHub:
git clone https://github.com/wang-lab/StiffCalc.git
- Install StiffCalc using Conda:
conda env create -f StiffCalc.yaml
conda activate stiffcalc
- You can run StiffCalc using the following command:
Rscript StiffCalc.r -i [input file] -o [output file]
-i [input file]
The input is a gene read counts file in TPM (transcripts per million) format. The file should have gene symbols as row names and sample names as column headers.
Example input format:
Symbol Sample1 Sample2 Sample3 Sample4 Sample5 Sample6
METTL25 101 116 127 141 122 118
C3orf79 2 0 1 0 0 1
THOC3 934 1043 794 921 871 829
AHI1 919 941 1033 908 802 769
SNX27 832 885 986 886 873 907
-o [output file]
The output is a file with stiffness predictions (soft or stiff) for each sample.
Example output format:
tumor_rigidity_label
Sample1 soft
Sample2 stiff
Sample3 soft
To test StiffCalc, an example input file is available at data/test.txt. Run the following command to generate the prediction:
Rscript StiffCalc.r -i data/test.txt -o results/prediction.txt
An output file will be generated under results/prediction.txt.
License under the GNU public library