Enter your Sample Size, Segregating Sites, Nucleotide Diversity (π), and Sequence Length into this Tajima's D Calculator to compute the D Statistic, Watterson's Theta, Pi Estimate, and an Interpretation of selection signals.
Tajima's D Statistic
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Watterson's Theta (θw)
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Pi Estimate (θπ)
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Variance of D
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Interpretation
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Tajima's D is a population genetics statistic that tests the neutral mutation hypothesis by comparing two estimates of genetic diversity: nucleotide diversity (π) and Watterson's theta (θw). It detects deviations from neutral evolution caused by selection or demographic changes.
D = 0 indicates neutrality, D > 0 suggests balancing selection or population bottleneck, and D < 0 indicates directional selection or population expansion. Values outside ±2 are typically considered statistically significant.
Nucleotide diversity (π) measures the average number of differences per site between sequences, while Watterson's theta (θw) estimates diversity based only on the number of segregating sites. Their comparison forms the basis of Tajima's D.
A minimum of 10-20 sequences is recommended, though larger samples (50+) provide more statistical power. Very small samples may give unreliable results due to high variance.
Sliding window analysis is useful for detecting localized selection or demographic effects across a longer genomic region. It reveals spatial patterns of selection that might be masked in genome-wide averages.
Yes, Tajima's D can detect balancing selection (positive values), directional/purifying selection (negative values), and demographic effects like population bottlenecks or expansions that mimic selection signatures.
Population structure, demographic history (bottlenecks, expansions), migration, recombination rate variation, and linkage to selected sites can all influence Tajima's D values independently of local selection.