Submitted:
28 October 2026
Posted:
30 October 2026
You are already at the latest version
Abstract
In this paper, we develop a non-Hermitian coupling method for integrating heterogeneous
datasets. Using the completeness of the root-vector system of the
operator associated with the coupled graph Laplacian, we construct a generalization of a
bi-orthogonal basis. Decomposing the trace functional into
regular and nilpotent parts, we elaborate an analogue of the gradient ascent and
descent method for the extremal trace problem. The central point of the concept is that the extremal values coincide with
the trace values and their difference yields an intrinsic
characteristic of dataset heterogeneity. The results are illustrated by
single-cell multi-omics integration, where the indicators distinguish stable
systems from stratified populations.
Keywords:
manifold alignment
; unsupervised topological alignment of single-cell multi-omics integration
; graph laplacian
; single cell RNA-seq
; single cell epigenomics
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