A Comparative Statistical Analysis of Genetic Distances. I - Estimation of Distances and of their Variances: Distribution of the Estimators

✍ Scribed by Dr. M. Katz

• Publisher: John Wiley and Sons
• Year: 2007
• Tongue: English
• Weight: 909 KB
• Volume: 30
• Category: Article
• ISSN: 0323-3847
• DOI: 10.1002/bimj.4710300511

✦ Synopsis

We present a Monte-Carlo simulation analysis of the statistical properties of absolute genetic distance and of Nei's minimum ahd standard genetic distances. The estimation of distances (bias) and of their variances is analysed as well aa the distributions of distance and variance estimators, taking into account both gamete and locus samplings. Both of Nei's statistics are non-linear when dietcmcecl are BmcJl and consequently the distributions of their estimators are extremely asymmetrical. It is difficult to find theoretical laws t h a t fit such aeymmetrical distributions.

Absolute genetic distance is linear and its distributions are better fit by a normal distribution.

When d i a t a w are medium or large, minimum distance and absolute distance distributions are close to a normal distribution, but those of the standard distance can never be considered as normal.

For large distances the jack-knife estimator of the standard distance variance is bad; another standard distance estimator is suggeated. Absolute distance, which has the best mathematical properties, is particularly interesting for small distances if the gamete sample size is large, even when the number of loci is small. When both distance and gamete sample size are small, this statistic is biased.