Structured exploratory data analysis: an evaluation of the use of three SEDA statistics in assessing mode of...

Several SEDA statistics are described and three of them (the Midparent-Child Correlation Coefficient, the Major Gene Index, and the Offspring Between Parents Function) are evaluated with respect to their ability to distinguish monogenic, polygenic and sporadic effects on quantitative traits. The MPCC, MGI, and OBP, used in combination, are sensitive but not specific in identifying monogenic inheritance. In our tests, traits determined by a simple type of polygenic inheritance were almost invariably classified as monogenic. Sporadic traits, on the other hand, were correctly identified in 84 percent of cases. The concurrent use of these SEDA statistics and two sibship variance tests yielded some improvement whenever the two procedures agreed (which happened about 50 percent of the time). These results suggest that under some circumstances, SEDA can be a valuable adjunct to other methods of genetic analysis. SEDA methodology also appears promising as an aid in understanding the contribution of various nongenetic factors to quantitative traits.