RNA assignment and segmentation geometry in Visium HD profiles of fibrostenotic Crohn's disease

Retrospective reuse of spatial transcriptomics often starts from a deposited bin-level Seurat object rather than the inputs needed to revisit upstream molecular processing. We tested whether image segmentation could support a defensible cell-like reconstruction under this constraint in two complete H&E-stained intestinal sections from a Visium HD study of Crohn's disease-associated fibrostenosis (GSE302569). The available data comprised 18,085 genes, 988,942 original 8 µm bins and 179,596,575 UMIs. We evaluated 20 segmentation configurations in the preserved image coordinate system using a common bin-centre assignment rule, without restarting Space Ranger or introducing higher-resolution expression. RNA assignment ranged from 0% to 74.68% in CD1 and 0% to 64.05% in CD2. Expansion increased recovery but did not eliminate merged regions, straight boundaries or within-bin ambiguity; approximately 70-73% of InstanSeg brightfield nuclear regions received no assigned RNA. All 38 non-empty configuration-slice combinations underwent native full-mode RCTD against the same nine-group scIBD reference. Mean slice-level RNA recovery was negatively associated with primary-component dominance across 19 configurations (descriptive Spearman ρ = −0.77). Neither dominant-call agreement nor concentrated RCTD support validates boundaries or cell identity. The observed limitations in RNA recovery, region geometry, and compositional support did not establish any tested configuration as a reliable single-cell reconstruction from these inputs. The findings identify limitations of retrospective single-cell reconstruction from the available binned inputs, not the impossibility of cell-resolved analysis from suitable original data.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-01
DOI
https://doi.org/10.64898/2026.10.27.762235
Primary Topic
Single-cell and spatial transcriptomics
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

RNA assignment and segmentation geometry in Visium HD profiles of fibrostenotic Crohn's disease

Federica Ungaro, Luca Massimino
4 links
bioRxiv (Cold Spring Harbor Laboratory)
Single-cell and spatial transcriptomics
preprint

RNA assignment and segmentation geometry in Visium HD profiles of fibrostenotic Crohn's disease

Federica Ungaro, Luca Massimino
preprint en

Abstract

Retrospective reuse of spatial transcriptomics often starts from a deposited bin-level Seurat object rather than the inputs needed to revisit upstream molecular processing. We tested whether image segmentation could support a defensible cell-like reconstruction under this constraint in two complete H&E-stained intestinal sections from a Visium HD study of Crohn's disease-associated fibrostenosis (GSE302569). The available data comprised 18,085 genes, 988,942 original 8 µm bins and 179,596,575 UMIs. We evaluated 20 segmentation configurations in the preserved image coordinate system using a common bin-centre assignment rule, without restarting Space Ranger or introducing higher-resolution expression. RNA assignment ranged from 0% to 74.68% in CD1 and 0% to 64.05% in CD2. Expansion increased recovery but did not eliminate merged regions, straight boundaries or within-bin ambiguity; approximately 70-73% of InstanSeg brightfield nuclear regions received no assigned RNA. All 38 non-empty configuration-slice combinations underwent native full-mode RCTD against the same nine-group scIBD reference. Mean slice-level RNA recovery was negatively associated with primary-component dominance across 19 configurations (descriptive Spearman ρ = −0.77). Neither dominant-call agreement nor concentrated RCTD support validates boundaries or cell identity. The observed limitations in RNA recovery, region geometry, and compositional support did not establish any tested configuration as a reliable single-cell reconstruction from these inputs. The findings identify limitations of retrospective single-cell reconstruction from the available binned inputs, not the impossibility of cell-resolved analysis from suitable original data.

bioRxiv (Cold Spring Harbor Laboratory)
IRCCS Ospedale San Raffaele (IT)
Good health and well-being
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon