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Recently, in April 2026, new AADR versions were released on Harvard Dataverse. Among the more important additions are the new compatibility datasets introduced for reducing platform-specific bias when co-analyzing ancient DNA generated with different experimental setups. This is especially relevant when combining data produced with different capture reagents such as Agilent (AG), Twist (TW), and shotgun (SG), because these can introduce systematic differences that may affect downstream analyses. The compatibility panels were added to minimize that problem and make mixed-platform datasets more directly comparable. ...

This post is a continuation of the previous one, where I demonstrated how to perform PCA with PLINK. While PLINK’s PCA is great for quick, exploratory analysis, smartpca (part of the EIGENSOFT toolset) is particularly common in population-genetic and ancient-DNA studies. Smartpca can be compiled from the EIGENSOFT source or installed through conda. I covered the installation process in this earlier post: From EIGENSTRAT to PACKEDPED. As before, I’ll use a small subset. The focus here is on the technical process. One key difference in this post is that I’ll perform Linkage Disequilibrium (LD) pruning, which reduces redundancy between correlated SNPs before PCA. ...