Login / Signup

Deciphering tissue structure and function using spatial transcriptomics.

Benjamin L WalkerZixuan CangHonglei RenEric Bourgain-ChangQing Nie
Published in: Communications biology (2022)
The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and transcriptional information in analysis of ST datasets. The wide diversity of approaches in aim, methodology and technology for ST provides great challenges in dissecting cellular functions in spatial contexts. Here, we synthesize and review the key problems in analysis of ST data and methods that are currently applied, while also expanding on open questions and areas of future development.
Keyphrases
  • single cell
  • gene expression
  • mental health
  • induced apoptosis
  • cell cycle arrest
  • signaling pathway
  • machine learning
  • current status
  • deep learning
  • endoplasmic reticulum stress
  • data analysis
  • heat stress