The SHARE package: SNP-Haplotype Adaptive REgression

Association studies have been widely used to identify genetic liability variants for complex diseases. While scanning the chromosomal region one SNP at a time may not fully explore linkage disequilibrium (LD), haplotype analyses tend to require a fairly large number of parameters, thus potentially losing power. Clustering algorithms, such as the cladistic approach, have been proposed to reduce the dimensionality, yet they have important limitations. We propose the SHARE algorithm (Dai et al., 2009) that seeks the most informative set of SNPs for genetic association in a targeted region by growing/shrinking haplotypes with one more/less SNP in a stepwise fashion, and comparing prediction errors of different models via cross-validation. This is the manual of the SHARE package.