bioRxivBioinformaticsPreprint
Empowering Integrative and Collaborative Exploration of Single-Cell and Spatial Multimodal Data with SGS
Tingting XiaiD, Jiahe Sun, Fang LuiD, Yongjiang Luo, Yudi Mao, Ling XuiD, Yi WangiD
Abstract
Recent advancements in single-cell and spatial omics technologies have revolutionized our ability to capture multiple modalities data at a genome-wide scale within individual cells. However, visualizing these large-scale, high-dimensional, and complex datasets poses significant challenges. Here, we present SGS, a user-friendly, collaborative and versatile browser for visualizing single-cell and spatial multiomics data. SGS incorporates a novel genome browser framework, flexible visualization modules and a multi-panel adaptive communication mechanism to enable the synchronous visualization of diverse datasets. Notably, SGS empowers users with advanced capabilities for comparative visualization, through features like scCompare, scMultiView, and dual-chromosome module. Additionally, by adopting the "workstation concept", SGS enables data fast visualization and collaborative exploration. We showcase the potential of SGS in the comparative visualization and coordinated exploration of mutlimodal data with two examples. SGS is publicly available at https://sgs.bioinfotoolkits.net/home.
- assay: spatial transcriptomics
- assay: scRNA-seq
- research focus: dimensionality reduction
- research focus: clustering
- research focus: benchmarking
- research focus: database / resource
- approach: experimental assay
- Citations
- 0
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