Evidence map›Paper›PMID 28133578›Full record

ArticlePeerJ2017

Selection and evaluation of reference genes for analysis of mouse

Tanya T Cheung, Mitchell K Weston, Megan J Wilson

Abstract read
In one paragraph

Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  4. Review
  5. Frontiers in molecular neuroscience · 2022
    Article
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  7. Article
  8. Article
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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

3 authors.

Tanya T CheungDepartment of Anatomy, University of Otago , Dunedin , New Zealand.
Mitchell K WestonDepartment of Anatomy, University of Otago , Dunedin , New Zealand.
Megan J WilsonDepartment of Anatomy, University of Otago , Dunedin , New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of the brain is sex-dimorphic, and as a result so are many neurological disorders. One approach for studying sex-dimorphic brain development is to measure gene expression in biological samples using RT-qPCR. However, the accuracy and consistency of this technique relies on the reference gene(s) selected. We analyzed the expression of ten reference genes in male and female samples over three stages of brain development, using popular algorithms NormFinder, GeNorm and Bestkeeper. The top ranked reference genes at each time point were further used to quantify gene expression of three sex-dimorphic genes (

Indexed as

BrainDevelopmentMiceReference geneRT-qpcrSex-dimorphic

Identifiers

PMID28133578
PMCPMC5251938

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.