组学
计算生物学
计算机科学
数据科学
生物信息学
生物
作者
Anjun Ma,Adam McDermaid,Jennifer Xu,Yuzhou Chang,Qin Ma
标识
DOI:10.1016/j.tibtech.2020.02.013
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI