Evidence map›Paper›PMID 37858253›Full record

ArticleGenome biology2023

GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership.

Peter Carbonetto, Kaixuan Luo, Abhishek Sarkar, Anthony Hung, Karl Tayeb, Sebastian Pott, Matthew Stephens

Abstract read
In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. A tonsil organoid model reveals Epstein-Barr virus-infected germinal center B cell states during primary infection.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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  11. Review
  12. Covariate-moderated Empirical Bayes Matrix Factorization.Advances in neural information processing systems · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Dissection and integration of bursty transcriptional dynamics for complex systems.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Peter CarbonettoDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0003-1144-6780
Kaixuan LuoDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.
Abhishek SarkarDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.
Anthony HungDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.
Karl TayebDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.
Sebastian PottDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.
Matthew StephensDepartment of Human Genetics, University of Chicago, Chicago, IL, USA. mstephens@uchicago.edu.

Funding

Genome analysis: statistical methods and applicationsR01HG002585 · NHGRI · UNIVERSITY OF WASHINGTON · PI MATTHEW STEPHENS · 2002 to 2026
$8.4M
Medical Scientist National Research Service AwardT32GM150375 · NIGMS · UNIVERSITY OF CHICAGO · PI Raghavendra G Mirmira · 2023 to 2026
$5.5M
Genetic Mechanisms and Evolution-RenewalT32GM139782 · NIGMS · UNIVERSITY OF CHICAGO · PI Francesca Luca, John Novembre · 2021 to 2026
$5.1M
NHGRI NIH HHS R01 HG002585NIGMS NIH HHS T32 GM139782NIGMS NIH HHS T32 GM150375
6 · The paper itself

Abstract

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.

Indexed as

Chromatin Immunoprecipitation SequencingSingle-Cell AnalysisAlgorithmsCluster AnalysisGene Expression ProfilingSequence Analysis, RNADifferential expression analysisDimensionality reductionGene expressionMatrix factorizationParts-based representationsSingle-cell ATAC-seqSingle-cell RNA-seqTopic modeling

Identifiers

PMID37858253
PMCPMC10588049

What OpenQuestion holds

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LicenceCC BY
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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.