Name
Abstract | ||
|---|---|---|
Pairs of individuals from a study cohort will often share long-range haplotypes identical-by-descent. Such haplotypes are transmitted from common ancestors that lived tens to hundreds of generations in the past, and they can now be efficiently detected in high-resolution genomic datasets, providing a novel source of information in several domains of genetic analysis. Recently, haplotype sharing distributions were studied in the context of demographic inference, and they were used to reconstruct recent demographic events in several populations. We here extend the framework to handle demographic models that contain multiple demes interacting through migration. We extensively test our formulation in several demographic scenarios, compare our approach with methods based on ancestry deconvolution and use this method to analyze Masai samples from the HapMap 3 dataset. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1093/bioinformatics/btt239 | BIOINFORMATICS |
Keywords | Field | DocType |
haplotypes,hapmap project,human migration | Human migration,Data mining,Source code,International HapMap Project,Inference,Computer science,Haplotype,Bioinformatics,Java,Haplotype estimation,Common descent | Journal |
Volume | Issue | ISSN |
29 | 13 | 1367-4803 |
Citations | PageRank | References |
2 | 0.47 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pier Francesco Palamara | 1 | 26 | 2.82 |
| Itsik Pe’er | 2 | 54 | 7.64 |