The Geography and Ethnicity of People’s Names

When sampling locations are known, the association between genetic and geographic distances can be tested by spatial autocorrelation or regression methods. These tests give some clues to the possible shape of the genetic landscape. Nevertheless, correlation analyses fail when attempting to identify where genetic barriers exist, namely, the areas where a given variable shows an abrupt rate of change. To this end, a computational geometry approach is more suitable because it provides the locations and the directions of barriers and because it can show where geographic patterns of two or more variables are similar. In this frame we have implemented Monmonier's (1973) maximum difference algorithm in a new software package to identify genetic barriers. To provide a more realistic representation of the barriers in a genetic landscape, we implemented in the software a significance test by means of bootstrap matrices analysis. As a result, the noise associated with genetic markers can be visualized on a geographic map and the areas where genetic barriers are more robust can be identified. Moreover, this multiple matrices approach can visualize the patterns of variation associated with different markers in the same overall picture. This improved Monmonier's method is highly reliable and can be applied to nongenetic data whenever sampling locations and a distance matrix between corresponding data are available.

An assessment was made of the usefulness and accuracy of a computer program for the identification of the south Asian population through the classification of names on a disease register. The computer program, Nam Pehchan, was used to classify names as either south Asian or non south Asian. The results were compared with a reference standard, which combined use of the program with visual inspection. The latter was facilitated by a computer-generated dictionary of common non south Asian names. The data set consisted of 356,555 cases of incident cancer (ICD9: 140-208) registered between 1990 and 1992 by Thames, Trent, West Midlands and Yorkshire cancer registries. Nam Pehchan classified 5506 cases as south Asian. Visual inspection identified 2024 false positives (36.8 per cent of all cases identified as south Asian by Nam Pehchan) and 363 false negatives (9.5 per cent of those identified by the reference standard). Compared with the reference standard, Nam Pehchan had a sensitivity of 90.5 per cent and a positive predictive value of 63.2 per cent. The Nam Pehchan program quickly identified a high proportion of the names classified as south Asian by the reference standard, but the high false positive rate means that the program alone is not an adequate single strategy. The time-consuming process of inspection of program negatives for large data sets can be substantially reduced by comparison with dictionaries of common non south Asian names.

Heritable surnames are highly diverse cultural markers of coancestry in human populations. A patrilineal surname is inherited in the same way as the non-recombining region of the Y chromosome and there should, therefore, be a correlation between the two. Studies of Y haplotypes within surnames, mostly of the British Isles, reveal high levels of coancestry among surname cohorts and the influence of confounding factors, including multiple founders for names, non-paternities and genetic drift. Combining molecular genetics and surname analysis illuminates population structure and history, has potential applications in forensic studies and, in the form of 'genetic genealogy', is an area of rapidly growing interest for the public.