Evidence map›Paper›PMID 36945441›Full record

ArticlebioRxiv : the preprint server for 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

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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

7 authors.

Peter CarbonettoDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.
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.

Funding

Genome analysis: statistical methods and applicationsR01HG002585 · NHGRI · UNIVERSITY OF WASHINGTON · PI MATTHEW STEPHENS · 2002 to 2026
$8.4M
NHGRI NIH HHS R01 HG002585
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

differential expression analysisdimensionality reductiongene expressionmatrix factorizationparts-based representationssingle-cell ATAC-seqsingle-cell RNA-seqtopic modeling

Identifiers

PMID36945441
PMCPMC10028846

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read31
Read underepoch 390

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 Socratic graph.