SOMDE: a scalable method for identifying spatially variable genes with self-organizing map | Zendy

Minsheng Hao | Zendy; Kui Hua | Zendy; Xuegong Zhang | Zendy

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SOMDE: a scalable method for identifying spatially variable genes with self-organizing map

Author(s) -

Minsheng Hao,

Kui Hua,

Xuegong Zhang

Publication year - 2021

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab471

Subject(s) - computer science , python (programming language) , scalability , source code , context (archaeology) , data mining , database , biology , programming language , paleontology

Recent developments of spatial transcriptomic sequencing technologies provide powerful tools for understanding cells in the physical context of tissue microenvironments. A fundamental task in spatial gene expression analysis is to identify genes with spatially variable expression patterns, or spatially variable genes (SVgenes). Several computational methods have been developed for this task. Their high computational complexity limited their scalability to the latest and future large-scale spatial expression data.

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