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To cite lilikoi in publications use:
Fang X, Liu Y, Ren Z, Du Y, Huang Q, Garmire LX (2020). “Lilikoi V2.0: a deep-learning enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data.” bioRxiv. doi:10.1101/2020.07.09.195677, https://doi.org/10.1101/2020.07.09.195677.
AlAkwaa FM, Yunits B, Huang S, Alhajaji H, Garmire LX (2018). “Lilikoi: an R package for personalized pathway-based classification modeling using metabolomics data.” GigaScience, 7(12). https://doi.org/10.1093/gigascience/giy136.
Corresponding BibTeX entries:
@Article{, title = {Lilikoi V2.0: a deep-learning enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data}, author = {Xinying Fang and Yu Liu and Zhijie Ren and Yuheng Du and Qianhui Huang and Lana X. Garmire}, journal = {bioRxiv}, year = {2020}, doi = {10.1101/2020.07.09.195677}, url = {https://doi.org/10.1101/2020.07.09.195677}, }
@Article{, title = {Lilikoi: an R package for personalized pathway-based classification modeling using metabolomics data}, author = {Fadhl M. AlAkwaa and Breck Yunits and Sijia Huang and Hassam Alhajaji and Lana X. Garmire}, journal = {GigaScience}, year = {2018}, volume = {7}, number = {12}, url = {https://doi.org/10.1093/gigascience/giy136}, }
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.