Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets

Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets

Abstract Multi‐omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi‐Omics Factor Analysis (MOFA), a computational method for discov...

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Bibliographic Details
Main Authors: Ricard Argelaguet, Britta Velten, Damien Arnol, Sascha Dietrich, Thorsten Zenz, John C Marioni, Florian Buettner, Wolfgang Huber, Oliver Stegle
Format: Article
Language:English
Published: Springer Nature 2018-06-01
Series:Molecular Systems Biology
Subjects:
data integration
dimensionality reduction
multi‐omics
personalized medicine
single‐cell omics
Online Access:https://doi.org/10.15252/msb.20178124
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https://doi.org/10.15252/msb.20178124

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