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AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments
In the integrative analyses of omics data, it is often of interest to extract data representation from one data type that best reflect its relations with another data type. This task is traditionally fulfilled by linear methods such as canonical correlation analysis (CCA) and partial least squares (...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8820645/ https://www.ncbi.nlm.nih.gov/pubmed/35081109 http://dx.doi.org/10.1371/journal.pcbi.1009826 |