MultiVI: deep generative model for the integration of multimodal data
University of California, Berkeley · Berkeley College · +4 more institutions
Abstract
Jointly profiling the transcriptome, chromatin accessibility and other molecular properties of single cells offers a powerful way to study cellular diversity. Here we present MultiVI, a probabilistic model to analyze such multiomic data and leverage it to enhance single-modality datasets. MultiVI creates a joint representation that allows an analysis of all modalities included in the multiomic input data, even for cells for which one or more modalities are missing. It is available at scvi-tools.org .
Citation impact
- FWCI
- 42.64
- Percentile
- 100%
- References
- 40
Authors
6- TATal AshuachCorresponding
University of California, Berkeley
- MIMariano I. Gabitto
Berkeley College, Ave Maria University, Allen Institute, University of California, Berkeley
- RVRohan V. Koodli
University of California, Berkeley
- GSGiuseppe-Antonio Saldi
Allen Institute for Brain Science, Allen Institute
- MIMichael I. Jordan
University of California, Berkeley
Topics & keywords
- Leverage (statistics)
- Computer science
- Profiling (computer programming)
- Generative model
- Modalities
- Artificial intelligence
- Modality (human–computer interaction)
- Data integration