Evidence map›Paper›PMID 34991671›Full record

ArticleGenome biology2022

scDALI: modeling allelic heterogeneity in single cells reveals context-specific genetic regulation.

Tobias Heinen, Stefano Secchia, James P Reddington, Bingqing Zhao, Eileen E M Furlong, Oliver Stegle

Abstract read
In one paragraph

Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  7. ASPEN: Robust detection of allelic dynamics in single cell RNA-seq.bioRxiv : the preprint server for biology · 2025
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  8. Review
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  12. Methods and Insights from Single-Cell Expression Quantitative Trait Loci.Annual review of genomics and human genetics · 2023
    Review
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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

6 authors.

Tobias Heinen *Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Stefano Secchia *Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
James P ReddingtonGenome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Bingqing ZhaoGenome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Eileen E M FurlongGenome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. furlong@embl.de.
Oliver StegleDivision of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. oliver.stegle@embl.de.ORCID 0000-0002-8818-7193

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While it is established that the functional impact of genetic variation can vary across cell types and states, capturing this diversity remains challenging. Current studies using bulk sequencing either ignore this heterogeneity or use sorted cell populations, reducing discovery and explanatory power. Here, we develop scDALI, a versatile computational framework that integrates information on cellular states with allelic quantifications of single-cell sequencing data to characterize cell-state-specific genetic effects. We apply scDALI to scATAC-seq profiles from developing F1 Drosophila embryos and scRNA-seq from differentiating human iPSCs, uncovering heterogeneous genetic effects in specific lineages, developmental stages, or cell types.

Indexed as

Induced Pluripotent Stem CellsSingle-Cell AnalysisGene Expression RegulationSingle-cell, Regulatory genomics, Statistical methods

Identifiers

PMID34991671
PMCPMC8734213

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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.