Abstract: Methods and apparatus for use in complex genetics classification are disclosed. In one illustrative example, a method is performed using data from a sample population which includes counts of individuals in the sample population associated with both a particular diploid haplotype pair and a particular genetic trait class. A correspondence to analysis (COA) on the data from the sample population is performed (at least in part) so as to determine a first plurality of n-dimensional coordinates for each diploid haplotype pair and a second plurality of n-dimensional coordinates for each genetic trait class. A linear or quadratic classification analysis is then performed based on the first and the second pluralities of n-dimensional coordinates and diploid haplotype pairs of the at least two genes from an individual sample. Advantageously, the individual sample can be accurately classified into one of the genetic trait classes using the method.

Abstract: Software methods for identifying associations between genetic information and particular genetic traits are described. A candidate single nucleotide polymorphism (SNP) combination is selected from a plurality of candidate SNP combinations for a gene associated with (or suspected to be associated with) a genetic trait. Haplotype data associated with this candidate SNP combination are read for a plurality of individuals and grouped into a positive-responding group and a negative-responding group based on whether a predetermined trait criteria for an individual is met. A statistical analysis on the grouped haplotype data is performed to obtain a statistical measurement associated with the candidate SNP combination. The acts of selecting, reading, grouping, and performing are repeated as necessary to identify the candidate SNP combination having the optimal statistical measurement (if one exists). In one approach, all possible SNP combinations are selected and statistically analyzed.