Integrative Methods and Practical Challenges for Single-Cell Multi-omics.

IF: 21.942

Cited by: 127

Abstract

Fast-developing single-cell multimodal omics (scMulti-omics) technologies enable the measurement of multiple modalities, such as DNA methylation, chromatin accessibility, RNA expression, protein abundance, gene perturbation, and spatial information, from the same cell. scMulti-omics can comprehensively explore and identify cell characteristics, while also presenting challenges to the development of computational methods and tools for integrative analyses. Here, we review these integrative methods and summarize the existing tools for studying a variety of scMulti-omics data. The various functionalities and practical challenges in using the available tools in the public domain are explored through several case studies. Finally, we identify remaining challenges and future trends in scMulti-omics modeling and analyses.

Keywords

smFISH

Seurat

Intron seqFISH

seqFISH+

Gene Expression

Omics

Slide-seq

osmFISH

MERFISH

MASC-seq

Spatial Transcriptomics

STARmap

analysis tools

integrative methods

single-cell multi-modality

single-cell sequencing technology

MeSH terms

Algorithms

Computational Biology

DNA Methylation

Genomics

Humans

Proteomics

Single-Cell Analysis

Authors

Ma, Anjun

McDermaid, Adam

Xu, Jennifer

Chang, Yuzhou

Ma, Qin

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