MultiMAP: dimensionality reduction and integration of multimodal data
| Autor: | Mika Sarkin Jain, Krzysztof Polanski, Cecilia Dominguez Conde, Xi Chen, Jongeun Park, Lira Mamanova, Andrew Knights, Rachel A. Botting, Emily Stephenson, Muzlifah Haniffa, Austen Lamacraft, Mirjana Efremova, Sarah A. Teichmann |
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| Přispěvatelé: | Efremova, Mirjana [0000-0002-8107-9974], Apollo - University of Cambridge Repository |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Genetic Markers
0303 health sciences QH301-705.5 1. No poverty Method Chromosome Mapping Genomics QH426-470 Chromatin 03 medical and health sciences 0302 clinical medicine Gene Expression Regulation Genetics Chromosomes Human Humans Single-Cell Analysis Biology (General) Transcriptome 030217 neurology & neurosurgery Algorithms Software 030304 developmental biology Transcription Factors |
| Zdroj: | Genome Biology, Vol 22, Iss 1, Pp 1-26 (2021) Genome Biology |
| Popis: | Multimodal data is rapidly growing in many fields of science and engineering, including single-cell biology. We introduce MultiMAP, a novel algorithm for dimensionality reduction and integration. MultiMAP can integrate any number of datasets, leverages features not present in all datasets, is not restricted to a linear mapping, allows the user to specify the influence of each dataset, and is extremely scalable to large datasets. We apply MultiMAP to single-cell transcriptomics, chromatin accessibility, methylation, and spatial data and show that it outperforms current approaches. On a new thymus dataset, we use MultiMAP to integrate cells along a temporal trajectory. This enables quantitative comparison of transcription factor expression and binding site accessibility over the course of T cell differentiation, revealing patterns of expression versus binding site opening kinetics. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02565-y. |
| Databáze: | OpenAIRE |
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