An efficient multiple-cell approach to automatic aneuploidy screening.

Abstract

We describe a statistical method of discriminating efficiently, on the basis of multiple-cell measurements without operator interaction, between chromosomally normal human cell lines and those either containing a single additional chromosome or missing one chromosome. We begin by defining hypothetical but realistic "confusion matrices," which give the probabilities of (1) assigning each chromosome to each of various possible groups and (2) rejecting it as unclassifiable. From these, false-positive and false-negative rates of 0.01 and 0.001, respectively, are found to be attainable by processing 16 to 32 cells if the average probability of misclassifying or rejecting individual chromosomes is 5% to 9% for "Denver" groups or 10% to 17% for homologous pairs. Since these values are probably within the reach of current technology, the method is a basis for a realistic, fully automatic screening system. We also show how the method can be extended to the detection of quite general types of chromosomally abnormal cell lines.