Cargando…

Effects of Single Nucleotide Polymorphism Marker Density on Haplotype Block Partition

Many researchers have found that one of the most important characteristics of the structure of linkage disequilibrium is that the human genome can be divided into non-overlapping block partitions in which only a small number of haplotypes are observed. The location and distribution of haplotype bloc...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Sun Ah, Yoo, Yun Joo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5287124/
https://www.ncbi.nlm.nih.gov/pubmed/28154511
http://dx.doi.org/10.5808/GI.2016.14.4.196
Descripción
Sumario:Many researchers have found that one of the most important characteristics of the structure of linkage disequilibrium is that the human genome can be divided into non-overlapping block partitions in which only a small number of haplotypes are observed. The location and distribution of haplotype blocks can be seen as a population property influenced by population genetic events such as selection, mutation, recombination and population structure. In this study, we investigate the effects of the density of markers relative to the full set of all polymorphisms in the region on the results of haplotype partitioning for five popular haplotype block partition methods: three methods in Haploview (confidence interval, four gamete test, and solid spine), MIG++ implemented in PLINK 1.9 and S-MIG++. We used several experimental datasets obtained by sampling subsets of single nucleotide polymorphism (SNP) markers of chromosome 22 region in the 1000 Genomes Project data and also the HapMap phase 3 data to compare the results of haplotype block partitions by five methods. With decreasing sampling ratio down to 20% of the original SNP markers, the total number of haplotype blocks decreases and the length of haplotype blocks increases for all algorithms. When we examined the marker-independence of the haplotype block locations constructed from the datasets of different density, the results using below 50% of the entire SNP markers were very different from the results using the entire SNP markers. We conclude that the haplotype block construction results should be used and interpreted carefully depending on the selection of markers and the purpose of the study.