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Analysis and Visualization of Spatial Transcriptomic Data.
Liu, Boxiang; Li, Yanjun; Zhang, Liang.
Affiliation
  • Liu B; Baidu Research, Sunnyvale, CA, United States.
  • Li Y; Baidu Research, Sunnyvale, CA, United States.
  • Zhang L; Baidu Research, Sunnyvale, CA, United States.
Front Genet ; 12: 785290, 2021.
Article in En | MEDLINE | ID: mdl-35154244
ABSTRACT
Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent technological innovation that measures transcriptomic information while preserving spatial information. Spatial transcriptomic data can be generated in several ways. RNA molecules are measured by in situ sequencing, in situ hybridization, or spatial barcoding to recover original spatial coordinates. The inclusion of spatial information expands the range of possibilities for analysis and visualization, and spurred the development of numerous novel methods. In this review, we summarize the core concepts of spatial genomics technology and provide a comprehensive review of current analysis and visualization methods for spatial transcriptomics.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Genet Year: 2021 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Genet Year: 2021 Document type: Article Affiliation country: United States