Evidence map›Paper›PMID 39558887›Full record

ReviewGlia2025

All the single cells: Single-cell transcriptomics/epigenomics experimental design and analysis considerations for glial biologists.

Katherine E Prater, Kevin Z Lin

Abstract readReview
In one paragraph

Review in Glia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Katherine E PraterDepartment of Neurology, School of Medicine, University of Washington, Seattle, Washington, USA.ORCID 0000-0001-8615-207X
Kevin Z LinDepartment of Biostatistics, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-1236-9847

Funding

Dissecting the role of sex-linked genes and APOE e4 risk in ADR01AG073918 · NIA · UNIVERSITY OF WASHINGTON · PI DISTECHE, CHRISTINE M., JAYADEV, SUMAN · 2021 to 2025
$5.9M
Regulation of diverse microglial phenotypes in neurodegenerationR56AG084128 · NIA · UNIVERSITY OF WASHINGTON · PI JAYADEV, SUMAN, YOUNG, JESSICA ELAINE · 2023 to 2023
$871k
NIA NIH HHS 1R56AG084128NIA NIH HHS 5R01AG073918NIA NIH HHS R01 AG073918NIA NIH HHS R56 AG084128Warren Alpert Foundation
6 · The paper itself

Abstract

Single-cell transcriptomics, epigenomics, and other 'omics applied at single-cell resolution can significantly advance hypotheses and understanding of glial biology. Omics technologies are revealing a large and growing number of new glial cell subtypes, defined by their gene expression profile. These subtypes have significant implications for understanding glial cell function, cell-cell communications, and glia-specific changes between homeostasis and conditions such as neurological disease. For many, the training in how to analyze, interpret, and understand these large datasets has been through reading and understanding literature from other fields like biostatistics. Here, we provide a primer for glial biologists on experimental design and analysis of single-cell RNA-seq datasets. Our goal is to further the understanding of why decisions are made about datasets and to enhance biologists' ability to interpret and critique their work and the work of others. We review the steps involved in single-cell analysis with a focus on decision points and particular notes for glia. The goal of this primer is to ensure that single-cell 'omics experiments continue to advance glial biology in a rigorous and replicable way.

Indexed as

EpigenomicsGene Expression ProfilingNeurogliaSingle-Cell AnalysisTranscriptomeAnimalsHumansanalysisgliamultiomeRNA‐seqsingle‐cellsingle‐nucleustranscriptomics

Identifiers

PMID39558887
PMCPMC11809281

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.