The Rayleigh Quotient and Contrastive Principal Component Analysis II
PCA) to find modes of variation in functional data. Together, these extensions expand the scope of contrastive PCA while unifying disparate fields of spatial and functional methods within a single conceptual and mathematical framework. We showcase the utility of these extensions with several examples drawn from genomics, analyzing gene expression in cancer and immune response to vaccination.
Authors
- Lior Pachter (ORCID: https://orcid.org/0000-0002-9164-6231)
- Kayla Jackson (ORCID: https://orcid.org/0000-0001-6483-0108)
- Maria Carilli (ORCID: https://orcid.org/0000-0002-8977-7224)
Institutions
- University of Southern California (US)
- California Institute of Technology (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-04-10
- DOI
- https://doi.org/10.64898/2026.04.08.717236
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation Graduate Research Fellowship Program