Newest papers

MultiPASE: Shape-Aware Comparative 3D Genome Analysis

N. Nipu, G. Johnson, C. Roth, D. Rogers, S. R. Starkenburg, C. R. Steadman, G. E. Marai · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.22786 · cited by 0 works (OpenAlex) · open-access PDF

Korean

3D 유전자 패트릭스 구조는 Hi-C 데이터에서 재구성된 유전자 패트릭스 구조는 크로마틴 조직에 대한 가치있는 통찰력을 제공하지만 조건과 시간 포인트에 걸쳐 그들을 비교하는 것은 소음, 변수 및 자발적 접근 방향으로 인해 여전히 도전적입니다. 최첨단 구조 비교 접근 방법은 종종 접촉 매트릭스 기반 요약에 의존합니다. 우리는 재구성 된 3D 유전자 구조의 공간 기하학을 보존하지 않고 유전자 수준의 공간 포인트 구름으로 대표되는 통합을 만들기 위해 MultiPASE를 제시합니다. 따라서, MultiPASE는 유전자 수준의 공간 포인트 구름으로 대표되는 재구성된 3D 유전자 구조의 비교 분석을위한 컴퓨팅 파이프라인입니다. MultiPASE는 원자

Machine translation (Meta M2M100); the English original follows.

Abstract

3D genome structures reconstructed from Hi-C data provide valuable insights into chromatin organization, but comparing them across conditions and time points remains challenging because of noise, variability, and arbitrary orientation. State-of-the-art comparison approaches often rely on contact-matrix-based summaries, which do not preserve the spatial geometry of the reconstructed structures and make integration with gene expression and chromatin accessibility difficult. There is therefore a need for robust structural alignment and spatial abstraction methods that support integrated analysis across conditions and time points. We present MultiPASE, a computational pipeline for comparative analysis of reconstructed 3D genome structures represented as gene-level spatial point clouds. MultiPASE aligns point clouds into a shared coordinate frame using coarse-to-fine rigid registration with PCA-based axis disambiguation and robust ICP refinement, then summarizes spatial organization using two complementary shape abstraction methods that produce stable, nested, multi-scale representations from dense core regions to broader structural extent. Using Hi-C-derived reconstructions from viral infection experiments, we show how the approach reveals condition-dependent structural changes that are difficult to interpret from raw 3D structures alone. By integrating spatial structure with gene expression and chromatin accessibility, MultiPASE supports interactive analysis of spatial organization and gene relocation patterns. A quantitative validation, reported in the Supplementary Materials, shows that the proposed shape abstractions preserve non-convex features, remain stable across samples, and that the alignment pipeline is necessary for meaningful comparison. A usage case and a usability evaluation with eight participants demonstrate the pipeline's effectiveness for comparative structural analysis.

Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese

Topics: Computer science, Chromatin, Abstraction, Pipeline (software), Point cloud, Computational biology

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange