Evidence map›Paper›PMID 35100368›Full record

ArticleG3 (Bethesda, Md.)2022

Testing the accuracy of 3D automatic landmarking via genome-wide association studies.

Yoland Savriama, Diethard Tautz

Open access · goldAbstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 25% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Yoland SavriamaDepartment Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, 24306 Plön, Germany.ORCID 0000-0002-9980-584X
Diethard TautzDepartment Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, 24306 Plön, Germany.ORCID 0000-0002-0460-5344
Max Planck Institute for Evolutionary Biology · DE

Funding

Genome-wide association studies in outbred miceR01GM097737 · NIGMS · UNIVERSITY OF CHICAGO · PI PALMER, ABRAHAM A · 2011 to 2014
$1.9M
NIGMS NIH HHS R01 GM097737
6 · The paper itself

Abstract

Various advances in 3D automatic phenotyping and landmark-based geometric morphometric methods have been made. While it is generally accepted that automatic landmarking compromises the capture of the biological variation, no studies have directly tested the actual impact of such landmarking approaches in analyses requiring a large number of specimens and for which the precision of phenotyping is crucial to extract an actual biological signal adequately. Here, we use a recently developed 3D atlas-based automatic landmarking method to test its accuracy in detecting QTLs associated with craniofacial development of the house mouse skull and lower jaws for a large number of specimens (circa 700) that were previously phenotyped via a semiautomatic landmarking method complemented with manual adjustment. We compare both landmarking methods with univariate and multivariate mapping of the skull and the lower jaws. We find that most significant SNPs and QTLs are not recovered based on the data derived from the automatic landmarking method. Our results thus confirm the notion that information is lost in the automated landmarking procedure although somewhat dependent on the analyzed structure. The automatic method seems to capture certain types of structures slightly better, such as lower jaws whose shape is almost entirely summarized by its outline and could be assimilated as a 2D flat object. By contrast, the more apparent 3D features exhibited by a structure such as the skull are not adequately captured by the automatic method. We conclude that using 3D atlas-based automatic landmarking methods requires careful consideration of the experimental question.

Indexed as

Genome-Wide Association StudyImaging, Three-DimensionalAlgorithmsAnimalsHeadMandibleMiceQuantitative Trait LociSkull3D landmarkingatlas-based segmentationautomatic phenotypinggeometric morphometricsGWASlower jawsMus musculus domesticusQTL mappingskull

Identifiers

PMID35100368
PMCPMC9210295
OpenAlexW4221033202

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.