Main use-cases | extended haplotype heterozygosity estimation and visualization | ||
Authors | Alexander Klassmann | Mathieu Gautier | Renaud Vitalis |
Latest version | 3.2.2 | ||
License | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] | ||
Website | https://www.google.com | ||
Code repository | https://gitlab.com/oneoverx/rehh | ||
Publication | https://doi.org/10.1111/1755-0998.12634 | ||
Tutorial authors | Karamoko Niaré | ||
Tutorial date | 12/11/2023 |
Insert tool title
Summary sheet
Purpose
This tool computes several metrics of positive selection signatures along the genome of an organism. These metrics include the Extended Haplotype Homozygosity (EHH), integrated EHH (IHH), site-specific EHH (EHHS), integrated EHHS (iES), integrated haplotype homozygosity score (iHS), ratio of EHHS (Rsb) and cross-population EHH (XP-EHH). EHH is defined as the probability that two randomly chosen chromosomes, carrying the core allele, are homozygous over a given surrounding chromosomal region. More details on the EHH can be found in the paper published by Sabeti et al. 2002. This istechnically a useful gemomic metrics in malaria, as the nature and length of shared haplotypes and EHH scores flanking an allele, such as a drug resistance mutation, show the ancestral relationship between mutants and how selective sweep survived recombinations over time.
Existing resources
- This tutorial give details on how to run the functions
Citation
@Article{,
author = {Mathieu Gautier and Renaud Vitalis},
title = {rehh: An R package to detect footprints of selection in
genome-wide SNP data from haplotype structure},
journal = {Bioinformatics},
year = {2012},
volume = {28},
number = {8},
pages = {1176-1177},
}
@Article{,
author = {Mathieu Gautier and Alexander Klassmann and Renaud
Vitalis},
title = {rehh 2.0: a reimplementation of the R package rehh to
detect positive selection from haplotype structure},
journal = {Molecular Ecology Resources},
year = {2017},
volume = {17},
number = {1},
pages = {78-90},
doi = {10.1111/1755-0998.12634},
}