OBJECTIVE EVALUATION MEASURES OF GENETIC MARKER SELECTION IN LARGE-SCALE SNP GENOTYPING

摘要

High-throughput single nucleotide polymorphism (SNP) genotyping systems provide two kinds of fluorescent signals detected from different alleles. In current technologies, the process of genotype discrimination requires subjective judgments by expert operators, even when using clustering algorithms. Here, we propose two evaluation measures to manage fluorescent scatter data with nonclear plot aggregation. The first is the marker ranking measure, which provides a ranking system for the SNP markers based on the distance between the scatter plot distribution and a user-defined ideal distribution. The second measure, called individual genotype membership, uses the membership probability of each genotype related to an individual plot in the scatter data. In verification experiments, the marker ranking measure determined the ranking of SNP markers correlated with the subjective order of SNP markers judged by an expert operator. The experiment using the individual genotype membership measure clarified that the total number of unclassified individuals was remarkably reduced compared to that of manually unclassified ones. These two evaluation measures were implemented as the GTAssist software. GTAssist provides objective standards and avoids subjective biases in SNP genotyping workflows.