Test statistics for detecting aneuploidy and hyperdiploidy.

Possible approaches to the analytical evaluation of ploidy patterns are discussed and two specific problems are considered: detection of early onset of aneuploidy and detection of moderate hyperdiploidy. A statistical model for a euploid DNA pattern is formulated in terms of a mixture distribution. A test statistic for detecting deviations from this pattern is defined, and its performance is evaluated for simulated data representing differing degrees of severity of aneuploidy. An analysis based on a discriminant function using order statistics of the sample cumulative distribution functions is proposed for detecting hyperdiploidy. This procedure has the advantage of being relatively distribution-free; its performance is evaluated for simulated data and is compared with that of its classical counterparts. Although the results reported are only preliminary, they indicate that tailor-made statistical analyses can provide early detection of aneuploidy and hyperdiploidy with known and acceptable error rates using clinically reasonable sample sizes.