Evidence map›Paper›PMID 42605020›Full record

ArticleJournal of anatomy2026

The impact of alignment and scaling on biological inferences from landmark-free morphometrics.

Lucy E Roberts, Marco Camaiti, Anjali Goswami

Abstract read
In one paragraph

Article in Journal of anatomy, 2026. 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
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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

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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.

No citing paper in PubMed yet.

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.

Lucy E RobertsNatural History Museum, London, UK.ORCID https://orcid.org/0000-0002-1293-8667
Marco CamaitiNatural History Museum, London, UK.ORCID https://orcid.org/0000-0002-7388-4586
Anjali GoswamiNatural History Museum, London, UK.ORCID https://orcid.org/0000-0001-9465-810X

Funding

Biotechnology and Biological Sciences Research Council BB/X014819/1Leverhulme Trust RPG-2021-424
6 · The paper itself

Abstract

Recent advances in shape quantification techniques have revolutionised the field of evolutionary morphology by providing a time-efficient alternative to well-established methods such as geometric morphometrics. In particular, landmark-free methods are at the forefront of new developments in shape analysis, but concerns over their reproducibility and sensitivity to non-biological variation have hindered more widespread adoption. A primary source of non-biological bias in shape analysis is misalignment and incorrect scaling of specimens, which can result in capturing anatomically incongruent aspects of shape in otherwise homologous structures. Here, we compare methods for mesh alignment and scaling using a recently described landmark-free approach, Deterministic Atlas Analysis (DAA). We find similarities between morphospaces derived from meshes aligned using most alignment protocols, but with large differences in variance structure. Surprisingly, the largest differences are not found between Procrustes-based and non-Procrustes-based approaches, but between the Procrustes-based method with internal scaling and all other alignment approaches. More broadly, scaling method has the greatest impact on shape variation captured by DAA. Based on these results, we make recommendations to ensure that alignment strategy maintains homology in landmark-free morphometry. As in all morphometric analyses, violating principles of homology can result in spurious or inaccurate biological inferences in macroevolutionary studies of anatomy and must be explicitly considered in designing methodological frameworks.

Indexed as

DAAdiffeomorphismhomologyinterpretationlandmark‐freemethodsmorphometricsshape

Identifiers

PMID42605020
PMCPMC13478407

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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.