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, 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-PH model and the deep-learning based Cox-nnet model. Additionally, Lilikoi v2.0 supports data preprocessing, exploratory analysis, pathway visualization and metabolite-pathway regression. In summary, Lilikoi v2.0 is a modern, comprehensive package to enable metabolomics analysis in R programming environment.

Keywords:

• classification
• prognosis
• survival
• prediction
• neural network
• deep learning
• modelling
• cox proportional hazards
• metabolomics
• pathway
• visualization

Read the peer-reviewed publication(s):

(PubMed: 33484242)

Related datasets:

doi:10.5524/100841 IsNewVersionOf doi:10.5524/100520

Additional information:

https://cran.r-project.org/package=lilikoi

http://dx.doi.org/10.21228/M86K6W

Github links:

https://github.com/lanagarmire/lilikoi2