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.
Keywords: classification; deep learning; metabolomics; neural network; pathway; prognosis; survival analysis; visualization.
© The Author(s) 2021. Published by Oxford University Press GigaScience.