Evidence map›Paper›PMID 36945478›Full record

ArticlebioRxiv : the preprint server for biology2023

Differential allelic representation (DAR) identifies candidate eQTLs and improves transcriptome analysis.

Lachlan Baer, Karissa Barthelson, John Postlethwait, David Adelson, Stephen Pederson, Michael Lardelli

Open access · greenFull text readPreprint
PubMed Full text at PMC Publisher
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, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Lachlan BaerSchool of Biological Sciences, University of Adelaide, Adelaide, SA, Australia.
Karissa BarthelsonSchool of Biological Sciences, University of Adelaide, Adelaide, SA, Australia.
John PostlethwaitInstitute of Neuroscience, University of Oregon, Eugene, OR, USA.
David AdelsonSchool of Biological Sciences, University of Adelaide, Adelaide, SA, Australia.
Stephen PedersonBlack Ochre Data Labs, Indigenous Genomics, Telethon Kids Institute, Adelaide, SA, Australia.
Michael LardelliSchool of Biological Sciences, University of Adelaide, Adelaide, SA, Australia.
The University of Adelaide · AUAustralian National University · AUFlinders University · AUUniversity of Oregon · US

Funding

Integrative translational discovery of vascular risk factors in aging and dementiaRF1AG051504 · NIA · MAYO CLINIC JACKSONVILLE · PI BU, GUOJUN, ERTEKIN-TANER, NILUFER · 2015 to 2019
$9.8M
TRANSGENIC MOUSE COREP01AG030128 · NIA · UNIVERSITY OF ILLINOIS AT CHICAGO · PI WEEBER, EDWIN JOHN · 2009 to 2013
$9.4M
NIA NIH HHS P01 AG030128NIA NIH HHS RF1 AG051504
6 · The paper itself

Abstract

In comparisons between mutant and wild-type genotypes, transcriptome analysis can reveal the direct impacts of a mutation, together with the homeostatic responses of the biological system. Recent studies have highlighted that, when homozygous mutations are studied in non-isogenic backgrounds, genes from the same chromosome as a mutation often appear over-represented among differentially expressed (DE) genes. One hypothesis suggests that DE genes chromosomally linked to a mutation may not reflect true biological responses to the mutation but, instead, result from differences in representation of expression quantitative trait loci (eQTLs) between sample groups selected on the basis of mutant or wild-type genotype. This is problematic when inclusion of spurious DE genes in a functional enrichment study results in incorrect inferences of mutation effect. Here we show that

Identifiers

PMID36945478
PMCPMC10028786
OpenAlexW4323307081

What OpenQuestion holds

Textfull text, public
LicenceCC BY
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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.