Research output per year
Research output per year
Personal profile
Research overview
Oscar Gaggiotti is a MASTS professor. His research focuses on the study of spatial patterns of genetic diversity to better understand the evolutionary and ecological processes responsible for their origin
and maintenance. To this end he develops ecologically realistic population genetics theory and methods using a framework based on the metapopulation paradigm and Bayesian statistics.
With his research group he has developed several statistical approaches that can simultaneously utilize the information provided by different types of data (genetic, demographic, environmental) and has applied them to two research problems:
- Statistical inference of the demographic history and ecology of populations,
- Study of local adaptation to understand the molecular bases of phenotypic variation.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being -
SDG 10 Reduced Inequalities -
SDG 13 Climate Action -
SDG 14 Life Below Water -
SDG 15 Life on Land
Fingerprint
Dive into the research topics where Oscar Gaggiotti is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Methods to estimate marine functional connectivity: a primer
Sturrock, A. M., Tanner, S. E., Arnaud‐Haond, S., Aguzzi, J., Barboza, F. R., Beger, M., Blanco, A., Brophy, D., Carreton, M., Childs, A., Costantini, F., Gaggiotti, O. E., Gillanders, B. M., González‐Irusta, J. M., Guizien, K., Guy‐Haim, T., Haase, S., Hunter, E., Kotta, J. & Lacroix, G. & 12 others, , 24 Jun 2026, In: Ecological Applications. 36, 4, e70273.Research output: Contribution to journal › Review article › peer-review
Open AccessFile -
The diffusion of cooperative and solo bubble net feeding in Canadian Pacific humpback whales
Wray, J., O'Mahony, É., Baer, G., Robinson, N., Dundas, A., Gaggiotti, O., Rendell, L. & Keen, E., Jan 2026, In: Proceedings of the Royal Society B: Biological Sciences. 293, 2063, p. 1-12 12 p., 20252409.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
A method for identifying local adaptation in structured populations
do O, I., Gaggiotti, O., de Villemereuil, P. & Goudet, J., 23 Sept 2025, In: PLoS Genetics. 21, 9, p. 1-21 21 p., e1011871.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
A method for identifying spatially divergent selection in structured populations
do O, I., Gaggiotti, O., de Villemereuil, P. & Goudet, J., 24 Feb 2025, bioRxiv, 27 p.Research output: Working paper › Preprint
Open Access -
Post-pleistocene colonisation rather than the contemporary environment has most influenced the current population structure of Scottish Atlantic salmon (Salmo salar)
Cowell, F., Gaggiotti, O. E. & Cauwelier, E., 1 Oct 2025, In: PLoS ONE. 20, 10, p. 1-16 16 p., e0333164.Research output: Contribution to journal › Article › peer-review
Open AccessFile
Datasets
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KLFDAPC: a supervised machine learning approach for spatial genetic structure analysis (code)
Gaggiotti, O. E. (Creator), GitHub, 2022
https://github.com/xinghuq/KLFDAPC
Dataset: Software
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Deciphering signatures of natural selection via deep learning (code)
Gaggiotti, O. E. (Creator), GitHub, 2022
https://github.com/xinghuq/DeepGenomeScan
Dataset: Software
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DNA in the deep: Comparative molecular ecology for the conservation of beaked whales (thesis data)
Onoufriou, A. (Creator), Carroll, E. L. (Creator) & Gaggiotti, O. E. (Creator), University of St Andrews, 25 Apr 2023
DOI: 10.17630/411968f3-6191-4789-8316-90fa2c3473c4, https://doi.org/10.17630/sta/487
Dataset: Thesis dataset
File -
Replication Data for the manuscript Selection on ancient genetic variants fuels repeated ecotype formation in bottlenose dolphins
Louis, M. (Creator), Galimberti, M. (Creator), Archer, F. (Creator), Berrow, S. (Creator), Brownlow, A. (Creator), Fallon, R. (Creator), Nykänen, M. (Creator), O'Brien, J. (Creator), Robertson, K. (Creator), Rosel, P. E. (Creator), Simon-Bouhet, B. (Creator), Wegmann, D. (Creator), Fontaine, M. (Creator), Foote, A. (Creator) & Gaggiotti, O. E. (Creator), Dataverse, 2021
DOI: 10.23708/Q2MYHE
Dataset
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Selection on ancestral genetic variation fuels repeated ecotype formation in bottlenose dolphins (code)
Gaggiotti, O. E. (Creator), GitHub, 2021
https://github.com/besibo/GhostAncestry
Dataset: Software
Projects
- 1 Finished
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Behaviour-Connect: H2020 Marie Curie IEF
Gaggiotti, O. (PI) & Carroll, E. (CoI)
Joint Research Centre European Commission
1/02/16 → 31/01/18
Project: Fellowship
Activities
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Deep Learning in Population Genetics
Gaggiotti, O. E. (Speaker)
3 Jul 2023Activity: Talk or presentation types › Invited talk
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Member of the examination panel for Habilitation to conduct research in France (HDR)
Gaggiotti, O. E. (External examiner)
19 Jun 2023Activity: Examination types › External examination
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Deep Learning in Population Genetics
Gaggiotti, O. E. (Speaker)
19 Jun 2023Activity: Talk or presentation types › Invited talk
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Using Information theory and machine learning to advance eco-evolutionary research
Gaggiotti, O. E. (Speaker)
17 Jan 2023Activity: Talk or presentation types › Invited talk
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Deep Learning in Population Genetics
Gaggiotti, O. E. (Speaker)
6 Jan 2023Activity: Talk or presentation types › Invited talk