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Many joint-SNVs (single-nucleotide variants) analysis methods were proposedto tackle the "missing heritability" problem, which emphasizes that the jointgenetic variants can explain more heritability of traits and diseases. However,there is still lack of a systematic comparison and investigation on therelative strengths and weaknesses of these methods. In this paper, we evaluatedtheir performance on extensive simulated data generated by varying sample size,linkage disequilibrium (LD), odds ratios (OR), and minor allele frequency(MAF), which aims to cover almost all scenarios encountered in practicalapplications. Results indicated that a method called Statistics-space BoundaryBased Test (S-space BBT) showed stronger detection power than other methods.Results on a real dataset of gastric cancer for Korean population also validatethe effectiveness of the S-space BBT method.

A Comparative Study of Joint-SNVs Analysis Methods and Detection of Susceptibility Genes for Gastric Cancer in Korean Population