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Cobolt: integrative analysis of multimodal single-cell sequencing data

A growing number of single-cell sequencing platforms enable joint profiling of multiple omics from the same cells. We present Cobolt, a novel method that not only allows for analyzing the data from joint-modality platforms, but provides a coherent framework for the integration of multiple datasets m...

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Detalles Bibliográficos
Autores principales: Gong, Boying, Zhou, Yun, Purdom, Elizabeth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8715620/
https://www.ncbi.nlm.nih.gov/pubmed/34963480
http://dx.doi.org/10.1186/s13059-021-02556-z
Descripción
Sumario:A growing number of single-cell sequencing platforms enable joint profiling of multiple omics from the same cells. We present Cobolt, a novel method that not only allows for analyzing the data from joint-modality platforms, but provides a coherent framework for the integration of multiple datasets measured on different modalities. We demonstrate its performance on multi-modality data of gene expression and chromatin accessibility and illustrate the integration abilities of Cobolt by jointly analyzing this multi-modality data with single-cell RNA-seq and ATAC-seq datasets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02556-z).