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Blocks were defined using the four gamete rule.
The haplotype blocks were defined using the solid spine of LD approach, using Haploview's internal tagging program.
Pairwise linkage disequilibrium (LD) based on the D' statistic was measured using Haploview.[15] LD blocks were defined using their default algorithm.[16] Sliding windows of 2 4 adjacent SNPs were used to test for association.
Haplotype blocks were defined using the method described in [ 30].
IL6R haplotype blocks were defined using the model described by Gabriel et al. [ 13].
The LD blocks were defined using Haploview (Version 4.2) [ 36], and the LD blocks were defined by the criteria of Gabriel et al. [ 37] to further pinpoint potential candidate genes affecting T-cell subpopulations.
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Given a gene, the genomic boundaries of its DHS-based regulatory block were defined using the most distal DHS connected to that gene.
Two other blocks (11 instances) were defined using only MOTIF SAMPLER and alignments, and a single block (10 instances) only by C LZ analysis.
Haplotype blocks (regions of strong linkage disequilibrium) were defined using the method of Gabriel et al. [21].
Haplotype blocks (regions of strong linkage disequilibrium) were defined using the confidence interval option of Haploview (Gabriel et al, 2002), with minor adjustments to include adjacent SNPs, but maintaining the cumulative frequency of the common haplotypes to >90%.
In this paper, we consider the case where measure values are discretized using a fuzzy partition, and we extend our method so as to mine multiple-level fuzzy blocks, that is, blocks that are defined using hierarchies and that characterize fuzzy measure values.
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