MultiVI: deep generative model for the integration of multimodal data
Tal Ashuach, Mariano I. Gabitto, Rohan V. Koodli, Giuseppe-Antonio Saldi, Michael I. Jordan, Nir Yosef
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 .
Topics & Concepts
Leverage (statistics)Computer scienceProfiling (computer programming)Generative modelModalitiesArtificial intelligenceModality (human–computer interaction)Data integrationExternal Data RepresentationGenerative grammarMachine learningComputational biologyData miningBiologyOperating systemSociologySocial scienceSingle-cell and spatial transcriptomicsGene expression and cancer classificationGene Regulatory Network Analysis