Evidence map›Paper›PMID 29511359›Full record

ArticleJournal of experimental neuroscience2018

Improving Reproducibility and Candidate Selection in Transcriptomics Using Meta-analysis.

Laurence A Brown, Stuart N Peirson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of experimental neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. 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

2 authors.

Laurence A BrownSleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, Sir William Dunn School of Pathology, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0001-8116-4100
Stuart N PeirsonSleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, Sir William Dunn School of Pathology, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0003-3653-834X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptomic experiments are often used in neuroscience to identify candidate genes of interest for further study. However, the lists of genes identified from comparable transcriptomic studies often show limited overlap. One approach to addressing this issue of reproducibility is to combine data from multiple studies in the form of a meta-analysis. Here, we discuss recent work in the field of circadian biology, where transcriptomic meta-analyses have been used to improve candidate gene selection. With the increasing availability of microarray and RNA-Seq data due to deposition in public databases, combined with freely available tools and code, transcriptomic meta-analysis provides an ideal example of how open data can benefit neuroscience research.

Indexed as

circadianMeta-analysisopen sciencereproducibilitytranscriptomics

Identifiers

PMID29511359
PMCPMC5833209

What OpenQuestion holds

Textmetadata
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.