
qpAdm rotation explained: the screening strategy and its false-discovery bill
The rotating protocol tests every candidate as source and outgroup in turn — elegant, recommended by the method's auditors, and carrying a measured 72–100% false-discovery rate when run without temporal discipline. What rotation is actually for.
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f4-statistics explained: the arithmetic under every ancient-DNA claim
f2, f3, f4 and D-statistics are the shared-drift arithmetic beneath qpAdm, qpWave and admixture graphs. What each statistic measures, how a four-population test works, and how to read Z-scores like the papers do.
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Running qpAdm in R with ADMIXTOOLS 2: a working tutorial
From genotype files to a tested model: f2 extraction, qpadm() and its output tables, the arguments that silently change results (allsnps, fudge_twice, constrained), and the protocol discipline the code will not enforce for you.
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qpAdm troubleshooting: the errors, warnings and weird outputs, decoded
Negative weights, SE 9.99, every model rejected, every model passing, infeasible popdrop rows, allsnps confusion — the standard failure gallery of qpAdm runs and what each symptom actually indicates.
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