Randomized Spatial PCA (RASP): A computationally efficient method for dimensionality reduction of high-resolution spatial transcriptomics data
Ian K. Gingerich, Brittany A. Goods, Hildreth Robert Frost, Jean Fan, Jean Fan, Jean Fan · 2025
Read Randomized Spatial PCA (RASP): A computationally efficient method for dimensionality reduction of high-resolution spatial transcriptomics data by Ian K. Gingerich, Brittany A. Goods, Hildreth Robert Frost, Jean Fan, Jean Fan, Jean Fan (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12707688.txt.
Description
Ian Gingerich, Brittany Goods, and Hildreth Robert Frost build RASP, a fast place-aware shrink way for gene place data. Their study appeared in twenty twenty-five. Place gene reads tell how cells sit and work in cloth, and zone finds are key to form grasp. RASP is not a pack tool it self; packs come from group its marks, with fine span set by a near graph and a smooth dial.
A two-step chance shrink and set smooth make it fast. Gainst six known ways on four read kinds, it tied or beat truth marks while it ran far fast. Wide dial sweeps are now fit to run.
Catalog record
| CREATOR | Ian K. Gingerich, Brittany A. Goods, Hildreth Robert Frost, Jean Fan, Jean Fan, Jean Fan |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 91 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |