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Effects of Single Nucleotide Polymorphism Marker Density on Haplotype Block Partition
1Department of Mathematics Education, Seoul National University, Seoul 08826, Korea.
Genomics & Informatics
|February 4, 2017
Summary
Haplotype block partitioning results vary significantly with marker density. Using fewer than 50% of single nucleotide polymorphism (SNP) markers can lead to substantially different haplotype block structures, necessitating careful interpretation.
Area of Science:
- Population Genetics
- Genomic Analysis
- Bioinformatics
Background:
- The human genome is characterized by linkage disequilibrium, often partitioned into haplotype blocks containing few haplotypes.
- Haplotype block structure is influenced by population genetic factors like selection, mutation, recombination, and population structure.
Purpose of the Study:
- To investigate how marker density affects haplotype block partitioning results.
- To compare the performance of five popular haplotype block partitioning methods under varying marker densities.
Main Methods:
- Utilized subsets of single nucleotide polymorphism (SNP) markers from chromosome 22 in the 1000 Genomes Project and HapMap phase 3 data.
- Applied five haplotype block partitioning algorithms: Haploview (confidence interval, four gamete test, solid spine), MIG++ (PLINK 1.9), and S-MIG++.
- Compared results across datasets with marker densities ranging from 100% down to 20% of the original SNP markers.
Main Results:
- Decreasing marker density led to a reduction in the total number of haplotype blocks and an increase in their length across all tested algorithms.
- Haplotype block locations derived from datasets with less than 50% of the total SNP markers showed significant divergence from those using the complete marker set.
- Marker density critically influences the stability and accuracy of identified haplotype blocks.
Conclusions:
- Haplotype block construction is sensitive to the density and selection of single nucleotide polymorphism (SNP) markers used.
- Results from haplotype block analyses should be interpreted with caution, considering the marker density and specific study objectives.
- The choice of markers significantly impacts the reliability of population genetic inferences based on haplotype blocks.
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