Parts-based decomposition of spatial genomics data finds distinct tissue regions.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 36611125.
- Also identified by DOI 10.1038/s41592-022-01725-7 and PMC identifier 9825081.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Dimension reduction is a cornerstone of exploratory data analysis; however, traditional methods fail to preserve the spatial context of spatial genomics data. In this work, we develop a nonnegative spatial factorization (NSF) model that allows interpretable, parts-based decomposition of spatial single-cell count data. NSF allows label-free annotation of regions of interest in spatial genomics data and identifies genes and cells that can be used to define those regions.
Medical subject headings
- Genomics