The spatial landscape of gene expression isoforms in tissue sections
In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT)…
Citation: Lebrigand K. et al (2023) "The spatial landscape of gene expression isoforms in tissue sections" Nucleic Acids Research https://academic.oup.com/nar/article/51/8/e47/7079641