ImmunoRankAge

A machine learning model for predicting immune age by rank-enrichment algorithm. This model, operating in both CPU and GPU modes, quickly predicts over 200 samples in less than 10 seconds.

Requirements

• R == 4.1.0
• data.table == 1.14.6
• matrixStats == 0.63.0
• python == 3.7.3
• pytorch == 1.14.0
• numpy == 1.21.6
• pandas == 1.3.5
• pytorch-tabnet == 4.0

Note: If cuda is available, GPU modes will be run automatically.

Tutorial

Git clone

git clone git://github.com/aapupu/ImmunoRankAge.git

Run in ImmunoRankAge folder

cd ImmunoRankAge

Run ImmunoRankAge

python ImmunoRankAge_main.py --file_path /path/to/RNAseq.txt --norwayname tpm/count

Output

• outs.csv: predicted immune age of sample.
• enrich_score.csv: enrichment score of input feature by rank-enrichment algorithm.

Citation

Deciphering Immunosenescence in PBMCs from Child to Frailty: Transcriptional Changes, Inflammation Dynamics, and Immune Age Predictive Modeling

Contacts

kyzy850520@163.com
luojh@jnu.edu.cn