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Reposted by Lucas Anchieri

Eduardo Amorim @cegamorim.bsky.social · 08/05/2026

Yesterday our article was featured on the cover of Nature. I'm incredibly proud of this team, led primarily by Latin Americans, & the result of the decade-long work by @hunemeier.bsky.social & lab. Kudos to the 1st authors too (incl @macscastro.bsky.social here on 🟦☁️) www.nature.com/nature/volum...

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Reposted by Lucas Anchieri

Eleni Seferidou @eleniseferidou.bsky.social · 21/04/2026

We (with @gatag.bsky.social) are happy to share our discussion, where we explore three cases of matrilocality and genetic matriline connections identified with ancient DNA. You can find the open access paper published in evolutionary human sciences: www.cambridge.org/core/journal...

cambridge.org

Exploring matrilocality in history: insights from ancient DNA | Evolutionary Human Sciences | Cambridge Core

Exploring matrilocality in history: insights from ancient DNA - Volume 8

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Reposted by Lucas Anchieri

Miren Iraeta Orbegozo @mireniraorb.bsky.social · 23/02/2026

Really excited to share our new paper on the Early Iron Age mass grave at Gomolava (9th c. BCE), a study I had the pleasure to work on during my PhD with an amazing group of co-authors across multiple disciplines. Open access link: www.nature.com/articles/s41... 🧵👇

nature.com

A large mass grave from the Early Iron Age indicates selective violence towards women and children in the Carpathian Basin - Nature Human Behaviour

In this analysis of biomolecular and archaeological data from a ninth-century BCE mass grave in the Carpathian Basin, Fibiger et al. find evidence for the targeted killing of mostly unrelated women an...

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Lucas Anchieri @anchieri.bsky.social · 08/02/2026

To sum up, the effect of the sampling is what we're testing here, and I am confident in our results and their presentation. I am very open to discussing it directly with you on Zoom, if you are interested. I feel like having an actual conversation would be more useful to both of us. Let me know!

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Lucas Anchieri @anchieri.bsky.social · 08/02/2026

It is true that some methods fare better with strong selection than others here, but I think the results from the first part with "ideal" data, and the way they are discussed in the discussion, offer enough context so as not to suggest that some methods are just always bad with strong selection

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Lucas Anchieri @anchieri.bsky.social · 08/02/2026

In the second part, we look at "ancient-like" data by focusing on a sampling scheme based on a real-life scenario. This one also produces streaks of fixed alleles for higher coefficients, albeit to a lesser extent than in the 1,000 gen. version of the "ideal" dataset (Fig. S2).

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Lucas Anchieri @anchieri.bsky.social · 08/02/2026

In that case, while weak selection is now more easily detectable, the sampling does not allow to estimate strong selection. The fact that this is an effect of the sampling is clearly, explicitly described in the figures, results, and discussion.

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Lucas Anchieri @anchieri.bsky.social · 08/02/2026

In this case, we do show that stronger selection is easier to estimate while weaker selection remains undetectable. On the opposite, the dataset covering a longer timespan (1,000 gen.) does produce a long streak of fixed alleles (Fig. S1). This corresponds to not removing the red part on your plot.

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Lucas Anchieri @anchieri.bsky.social · 08/02/2026

I think that last statement oversimplifies what the results show. We assess several sampling strategies. In the first part with "ideal" data, the dataset covering a "short" timespan (100 gen.) corresponds in practice to what you suggest to do on your plot for large selection coeffs. (see Fig. S1).

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Lucas Anchieri @anchieri.bsky.social · 06/02/2026

When sampling over a long period of time, the trajectory can reach fixation too quickly to be effectively covered, and the subsequent streak of time points with a frequency of 1 in itself is uninformative. All methods, not just BMWS, struggle to estimate stronger selection coefficients in that case

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Lucas Anchieri @anchieri.bsky.social · 06/02/2026

We actually discussed a lot about that and decided to keep all simulations. We thought that applying any type of conditioning on loss/fixation would also introduce some kind of bias, as we wanted to also test cases with “bad” trajectories. What you mention here is precisely what our results show.

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Reposted by Lucas Anchieri

Bioinformatics Advances @bioinfoadv.bsky.social · 03/02/2026

🧬 Now published in Bioinformatics Advances: "pygenstrat: A Python package for EIGENSTRAT data processing" by @dilekopter.bsky.social Full article available: doi.org/10.1093/bioadv/vbag022

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Lucas Anchieri @anchieri.bsky.social · 13/11/2024

Thanks for putting this together!! I would be happy to be part of the list as well

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Reposted by Lucas Anchieri

AaRC @aarc-community.bsky.social · 13/11/2024

With all the new people migrating into BlueSky, we have created a small starter pack for aDNA (and other molecules) researchers. go.bsky.app/F4EPLJh 🧪🏺 #evosky #PaleoSky

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