Nova-ST: Nano-Patterned Ultra-Dense platform for spatial transcriptomics [Nova-ST](Dataset ID: STDS0000325)

0
|
98
|
9
Summary
Data
Sample
Catalog
Dataset information
Contributors
Accessions
How to cite
Dataset information
Summary:
Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost.
Overall design:
6-8 week old C57BL/6J mice were used for these experiments. Five coronal brain sections were taken and Nova-ST spatial transcriptomics libraries were created
Technology:
ST
Platform:
NextSeq 2000
Species:
Mus musculus
Tissues:
Brain
Submission date: 2024-02-22Update date: 2024-10-09
DOI: To be continue
Contributors
Davie, Kristofer James; Poovathingal, Suresh; Davie, Kristofer; Borm, Lars E; Vandepoel, Roel; Poulvellarie, Nicholas; Verfaillie, Annelien; Corthout, Nikky; Aerts, Stein
Contact: contrib1
Accessions
GEO Series Accessions: GSE256318
How to cite
  • Cite database of STOmicsDB:
    [1] Xu, Zhicheng et al. "STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization." Nucleic acids research vol. 52,D1 (2024): D1053-D1061. doi: 10.1093/nar/gkad933'
  • Cite visualization dataset:
    [2] Davie, Kristofer James. Nova-ST: Nano-Patterned Ultra-Dense platform for spatial transcriptomics [Nova-ST][DS/OL]. STOmicsDB, 2024[2024-02-22]. https://db.cngb.org/stomics/datasets/STDS0000325/. doi: xxxxxx
    #Format: {contributors}. {title}[DS/OL]. STOmicsDB, {the year of submission data}[{submission data}]. {dataset link}. doi: {doi ID}
  • Cite original data article:
    No results.