A Note on Two-Sample Tests for Comparing Intra-Individual Genetic Sequence Diversity between Populations
Article first published online: 24 SEP 2012
© 2012, The International Biometric Society
Volume 68, Issue 4, pages 1323–1326, December 2012
How to Cite
Giorgi, E. E. and Bhattacharya, T. (2012), A Note on Two-Sample Tests for Comparing Intra-Individual Genetic Sequence Diversity between Populations. Biometrics, 68: 1323–1326. doi: 10.1111/j.1541-0420.2012.01775.x
- Issue published online: 21 DEC 2012
- Article first published online: 24 SEP 2012
- Received February 2011. Revised December 2011. Accepted December 2011.
- HIV genetic diversity;
- Hypothesis testing;
- Nonparametric statistics;
- Two-sample test;
Summary Gilbert, Rossini, and Shankarappa (2005, Biometrics 61, 106-117) present four U-statistic based tests to compare genetic diversity between different samples. The proposed tests improved upon previously used methods by accounting for the correlations in the data. We find, however, that the same correlations introduce an unacceptable bias in the sample estimators used for the variance and covariance of the inter-sequence genetic distances for modest sample sizes. Here, we compute unbiased estimators for these and test the resulting improvement using simulated data. We also show that, contrary to the claims in Gilbert et al., it is not always possible to apply the Welch–Satterthwaite approximate t-test, and we provide explicit formulas for the degrees of freedom to be used when, on the other hand, such approximation is indeed possible.