Inferring Recombination Patterns In African Populations. Eeden, G., Uren, C., Möller, M., & Henn, B. M. Human Molecular Genetics, January, 2021. doi abstract bibtex While several high-resolution recombination maps exist for European-descent populations, the recombination landscape of African populations remains relatively understudied. Given that there is high genetic divergence among groups in Africa, it is possible that recombination hotspots also diverge significantly. Both limitations and opportunities exist for developing recombination maps for these populations. In this review, we discuss various recombination inference methods, and the strengths and weaknesses of these methods in analysing recombination in African-descent populations. Furthermore, we provide a decision tree and recommendations for which inference method to use in various research contexts. Establishing an appropriate methodology for recombination rate inference in a particular study will improve the accuracy of various downstream analyses including but not limited to local ancestry inference, haplotype phasing, fine-mapping of GWAS loci and genome assemblies.
@article{eeden_inferring_2021,
title = {Inferring {Recombination} {Patterns} {In} {African} {Populations}},
issn = {1460-2083},
doi = {10.1093/hmg/ddab020},
abstract = {While several high-resolution recombination maps exist for European-descent populations, the recombination landscape of African populations remains relatively understudied. Given that there is high genetic divergence among groups in Africa, it is possible that recombination hotspots also diverge significantly. Both limitations and opportunities exist for developing recombination maps for these populations. In this review, we discuss various recombination inference methods, and the strengths and weaknesses of these methods in analysing recombination in African-descent populations. Furthermore, we provide a decision tree and recommendations for which inference method to use in various research contexts. Establishing an appropriate methodology for recombination rate inference in a particular study will improve the accuracy of various downstream analyses including but not limited to local ancestry inference, haplotype phasing, fine-mapping of GWAS loci and genome assemblies.},
language = {eng},
journal = {Human Molecular Genetics},
author = {Eeden, Gerald and Uren, Caitlin and Möller, Marlo and Henn, Brenna M.},
month = jan,
year = {2021},
pmid = {33445180},
}
Downloads: 0
{"_id":"MYg8WDk6hdwe3u8wy","bibbaseid":"eeden-uren-mller-henn-inferringrecombinationpatternsinafricanpopulations-2021","authorIDs":[],"author_short":["Eeden, G.","Uren, C.","Möller, M.","Henn, B. M."],"bibdata":{"bibtype":"article","type":"article","title":"Inferring Recombination Patterns In African Populations","issn":"1460-2083","doi":"10.1093/hmg/ddab020","abstract":"While several high-resolution recombination maps exist for European-descent populations, the recombination landscape of African populations remains relatively understudied. Given that there is high genetic divergence among groups in Africa, it is possible that recombination hotspots also diverge significantly. Both limitations and opportunities exist for developing recombination maps for these populations. In this review, we discuss various recombination inference methods, and the strengths and weaknesses of these methods in analysing recombination in African-descent populations. Furthermore, we provide a decision tree and recommendations for which inference method to use in various research contexts. Establishing an appropriate methodology for recombination rate inference in a particular study will improve the accuracy of various downstream analyses including but not limited to local ancestry inference, haplotype phasing, fine-mapping of GWAS loci and genome assemblies.","language":"eng","journal":"Human Molecular Genetics","author":[{"propositions":[],"lastnames":["Eeden"],"firstnames":["Gerald"],"suffixes":[]},{"propositions":[],"lastnames":["Uren"],"firstnames":["Caitlin"],"suffixes":[]},{"propositions":[],"lastnames":["Möller"],"firstnames":["Marlo"],"suffixes":[]},{"propositions":[],"lastnames":["Henn"],"firstnames":["Brenna","M."],"suffixes":[]}],"month":"January","year":"2021","pmid":"33445180","bibtex":"@article{eeden_inferring_2021,\n\ttitle = {Inferring {Recombination} {Patterns} {In} {African} {Populations}},\n\tissn = {1460-2083},\n\tdoi = {10.1093/hmg/ddab020},\n\tabstract = {While several high-resolution recombination maps exist for European-descent populations, the recombination landscape of African populations remains relatively understudied. Given that there is high genetic divergence among groups in Africa, it is possible that recombination hotspots also diverge significantly. Both limitations and opportunities exist for developing recombination maps for these populations. In this review, we discuss various recombination inference methods, and the strengths and weaknesses of these methods in analysing recombination in African-descent populations. Furthermore, we provide a decision tree and recommendations for which inference method to use in various research contexts. Establishing an appropriate methodology for recombination rate inference in a particular study will improve the accuracy of various downstream analyses including but not limited to local ancestry inference, haplotype phasing, fine-mapping of GWAS loci and genome assemblies.},\n\tlanguage = {eng},\n\tjournal = {Human Molecular Genetics},\n\tauthor = {Eeden, Gerald and Uren, Caitlin and Möller, Marlo and Henn, Brenna M.},\n\tmonth = jan,\n\tyear = {2021},\n\tpmid = {33445180},\n}\n\n","author_short":["Eeden, G.","Uren, C.","Möller, M.","Henn, B. M."],"key":"eeden_inferring_2021","id":"eeden_inferring_2021","bibbaseid":"eeden-uren-mller-henn-inferringrecombinationpatternsinafricanpopulations-2021","role":"author","urls":{},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"http://bibbase.org/zotero/TBHostGen","creationDate":"2021-03-11T08:09:47.316Z","downloads":0,"keywords":[],"search_terms":["inferring","recombination","patterns","african","populations","eeden","uren","möller","henn"],"title":"Inferring Recombination Patterns In African Populations","year":2021,"dataSources":["csPxbBZ9RG8CqYnrf"]}