GAN-GMHI GAN-GMHI: A Deep Learning Approach for Predicting Phenotype from Gut Microbiome Data

Gut microbiome-based health index (GMHI) has been applied with success, while the discrimination powers of GMHI varied for different diseases, limiting its utility on a broad-spectrum of diseases. In this work, a generative adversarial network (GAN) model is proposed to improve the discrimination power of GMHI. Built based on the batch corrected data through GAN, GAN-GMHI has largely reduced the batch effects, and profoundly improved the performance for distinguishing healthy individuals and different diseases. GAN-GMHI has provided a solution to unravel the strong association of gut microbiome and diseases, and indicated a more accurate venue toward microbiome-based disease monitoring. The code for GAN-GMHI is available at https://github.com/HUST-NingKang-Lab/GAN-GMHI.