Evidence map›Paper›PMID 41279463›Full record

ArticlebioRxiv : the preprint server for biology2025

GRASS-NB: Group-structured variable selection for spatial negative binomial data with applications to cancer registry and spatial omics.

Chloe Mattila, Brian Neelon, Kalyani Sonawane, Sha Cao, Peggi Angel, Elizabeth Hill, Souvik Seal

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Chloe MattilaDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Brian NeelonDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Kalyani SonawaneDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Sha CaoDepartment of Biomedical Engineering, Oregon Health Science University, Portland, Oregon, USA.
Peggi AngelDepartment of Pharmacology and Immunology, Medical University of South Carolina, Charleston, SC, USA.
Elizabeth HillDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Souvik SealDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.

Funding

Translational Science Laboratory Shared ResourceP30CA138313 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI John J Lemasters · 2009 to 2026
$42.7M
Spatial stromal proteomic biosignatures of DCIS risk and progressionR21CA286287 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ANGEL, PEGGI M · 2024 to 2024
$380k
NCI NIH HHS P30 CA138313NCI NIH HHS R21 CA286287
6 · The paper itself

Abstract

Spatially structured, overdispersed count data with high-dimensional predictors are increasingly observed across studies from population-level epidemiology to cellular-level spatial omics. Feature selection is critical to identify influential predictors, such as key risk factors or biomarkers. Few Bayesian studies have assessed negative binomial regression (NBR) models with standard variable selection priors, like the mixture

Indexed as

hierarchical shrinkagehorseshoe priornegative binomial distributionspatial count dataspike and slab prior

Identifiers

PMID41279463
PMCPMC12633453

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.