Evidence map›Paper›PMID 40949971›Full record

ArticlebioRxiv : the preprint server for biology2025

ASPEN: Robust detection of allelic dynamics in single cell RNA-seq.

Veronika Petrova, Muqing Niu, Thomas Vierbuchen, Emily S Wong

Abstract readPreprint
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

5 · Who and what money

Authors and funding

4 authors.

Veronika PetrovaVictor Chang Cardiac Research Institute, Sydney 2010, Australia.
Muqing NiuVictor Chang Cardiac Research Institute, Sydney 2010, Australia.
Thomas VierbuchenDevelopmental Biology Program, Sloan Kettering Institute for Cancer Research, New York, NY 10065, USA.ORCID 0000-0002-5690-5680
Emily S WongVictor Chang Cardiac Research Institute, Sydney 2010, Australia.ORCID 0000-0003-0315-2942

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Chemical Genetic Dissection of SWI/SNF Chromatin Remodeling Complex Functions in Cerebral Cortex DevelopmentR01NS126921 · NINDS · SLOAN-KETTERING INST CAN RESEARCH · PI LORENZ P. STUDER · 2023 to 2026
$2.1M
NCI NIH HHS P30 CA008748NINDS NIH HHS R01 NS126921
6 · The paper itself

Abstract

Single-cell RNA-seq data from F1 hybrids provides a unique framework for dissecting complex regulatory phenomena, but allelic measurements are limited by technical noise. Here, we present ASPEN, a statistical method for modeling allelic mean and variance in single-cell transcriptomic data from F1 hybrids. ASPEN uses a sensitive mapping pipeline and adaptive shrinkage to distinguish allelic imbalance and variance in single cells. Through extensive simulation based on sparse droplet-based single-cell data, ASPEN demonstrates improved sensitivity and control of false discoveries compared to existing approaches. Applied to mouse brain organoids and T cells, ASPEN identifies genes with incomplete X inactivation, stochastic monoallelic expression, and significant deviations in allelic variance. This reveals reduced variance in essential cellular pathways, and increased variance in neurodevelopmental and immune-specific genes.

Identifiers

PMID40949971
PMCPMC12424800

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Registered trials

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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.