Evidence map›Paper›PMID 30657194›Full record

ReviewGenetic epidemiology2019

Spinning convincing stories for both true and false association signals.

Richard J Biedrzycki, Ashley E Sier, Dongjing Liu, Erika N Dreikorn, Daniel E Weeks

Abstract readReview
In one paragraph

Review in Genetic epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

5 authors.

Richard J BiedrzyckiDepartment of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
Ashley E SierDepartment of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
Dongjing LiuDepartment of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
Erika N DreikornDepartment of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
Daniel E WeeksDepartment of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.ORCID 0000-0001-9410-7228

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When interpreting genome-wide association peaks, it is common to annotate each peak by searching for genes with plausible relationships to the trait. However, "all that glitters is not gold"-one might interpret apparent patterns in the data as plausible even when the peak is a false positive. Accordingly, we sought to see how human annotators interpreted association results containing a mixture of peaks from both the original trait and a genetically uncorrelated "synthetic" trait. Two of us prepared a mix of original and synthetic peaks of three significance categories from five different scans along with relevant literature search results and then we all annotated these regions. Three annotators also scored the strength of evidence connecting each peak to the scanned trait and the likelihood of further studying that region. While annotators found original peaks to have stronger evidence (p

Indexed as

Data CurationData Interpretation, StatisticalFalse Positive ReactionsDeceptionGenome-Wide Association StudyHumansPhenotypePolymorphism, Single Nucleotideassociation peaksfalse positivesgenome-wide association studiesliterature review

Identifiers

PMID30657194
PMCPMC6590226

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.