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BACKGROUND : previously we developed Lilikoi, a personalized pathway-based method to classify diseases using metabolomics data. Given the new trends of computation in the metabolomics field, it is important to update Lilikoi software.

RESULTS : here we report the next version of Lilikoi as a significant upgrade. The new Lilikoi v2.0 R package has implemented a deep learning method for classification, in addition to popular machine learning methods. It also has several new modules, including the most significant addition of prognosis prediction, implemented by Cox-proportional hazards model and the deep learning-based Cox-nnet model. Additionally, Lilikoi v2.0 supports data preprocessing, exploratory analysis, pathway visualization, and metabolite pathway regression.

CONCULSION : Lilikoi v2.0 is a modern, comprehensive package to enable metabolomics analysis in R programming environment.

Fang Xinying, Liu Yu, Ren Zhijie, Du Yuheng, Huang Qianhui, Garmire Lana X


classification, deep learning, metabolomics, neural network, pathway, prognosis, survival analysis, visualization