Article

MultiPLIER: a transfer learning framework for transcriptomics reveals systemic features of rare disease

2018-08-20

Abstract excerpt

<h4>SUMMARY</h4> Unsupervised machine learning methods provide a promising means to analyze and interpret large datasets. However, most gene expression datasets generated by individual researchers remain too small to fully benefit from these methods. In the case of rare diseases, there may be too few cases available, even when multiple studies are combined. We trained a Pathway Level Information ExtractoR (PLIER)...

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Literature Corpus work: 6400769c-de08-5b3b-a9aa-c0606da85abb
DOI: 10.1101/395947

Open publication

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