Using multi-way admixture mapping to elucidate TB susceptibility in the South African Coloured population. Daya, M., van der Merwe, L., Gignoux, C. R., van Helden, P. D., Möller, M., & Hoal, E. G. BMC genomics, 15:1021, 2014. 00000 doi abstract bibtex BACKGROUND: The admixed South African Coloured population is ideally suited to the discovery of tuberculosis susceptibility genetic variants and their probable ethnic origins, but previous attempts at finding such variants using genome-wide admixture mapping were hampered by the inaccuracy of local ancestry inference. In this study, we infer local ancestry using the novel algorithm implemented in RFMix, with the emphasis on identifying regions of excess San or Bantu ancestry, which we hypothesize may harbour TB susceptibility genes. RESULTS: Using simulated data, we demonstrate reasonable accuracy of local ancestry inference by RFMix, with a tendency towards miss-calling San ancestry as Bantu. Regions with either excess San ancestry or excess African (San or Bantu) ancestry are less likely to be affected by this bias, and we therefore proceeded to identify such regions, found in cases but not in controls (642 cases and 91 controls). A number of promising regions were found (overall p-values of 7.19×10-5 for San ancestry and \textless2.00×10-16 for African ancestry), including chromosomes 15q15 and 17q22, which are close to genomic regions previously implicated in TB. Promising immune-related susceptibility genes such as the GADD45A, OSM and B7-H5 genes are also harboured in the identified regions. CONCLUSION: Admixture mapping is feasible in the South African Coloured population and a number of novel TB susceptibility genomic regions were uncovered.
@article{daya_using_2014,
title = {Using multi-way admixture mapping to elucidate {TB} susceptibility in the {South} {African} {Coloured} population},
volume = {15},
issn = {1471-2164},
doi = {10.1186/1471-2164-15-1021},
abstract = {BACKGROUND: The admixed South African Coloured population is ideally suited to the discovery of tuberculosis susceptibility genetic variants and their probable ethnic origins, but previous attempts at finding such variants using genome-wide admixture mapping were hampered by the inaccuracy of local ancestry inference. In this study, we infer local ancestry using the novel algorithm implemented in RFMix, with the emphasis on identifying regions of excess San or Bantu ancestry, which we hypothesize may harbour TB susceptibility genes.
RESULTS: Using simulated data, we demonstrate reasonable accuracy of local ancestry inference by RFMix, with a tendency towards miss-calling San ancestry as Bantu. Regions with either excess San ancestry or excess African (San or Bantu) ancestry are less likely to be affected by this bias, and we therefore proceeded to identify such regions, found in cases but not in controls (642 cases and 91 controls). A number of promising regions were found (overall p-values of 7.19×10-5 for San ancestry and {\textless}2.00×10-16 for African ancestry), including chromosomes 15q15 and 17q22, which are close to genomic regions previously implicated in TB. Promising immune-related susceptibility genes such as the GADD45A, OSM and B7-H5 genes are also harboured in the identified regions.
CONCLUSION: Admixture mapping is feasible in the South African Coloured population and a number of novel TB susceptibility genomic regions were uncovered.},
language = {eng},
journal = {BMC genomics},
author = {Daya, Michelle and van der Merwe, Lize and Gignoux, Christopher R. and van Helden, Paul D. and Möller, Marlo and Hoal, Eileen G.},
year = {2014},
pmid = {25422094},
pmcid = {PMC4256931},
note = {00000 },
pages = {1021},
}
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In this study, we infer local ancestry using the novel algorithm implemented in RFMix, with the emphasis on identifying regions of excess San or Bantu ancestry, which we hypothesize may harbour TB susceptibility genes. RESULTS: Using simulated data, we demonstrate reasonable accuracy of local ancestry inference by RFMix, with a tendency towards miss-calling San ancestry as Bantu. Regions with either excess San ancestry or excess African (San or Bantu) ancestry are less likely to be affected by this bias, and we therefore proceeded to identify such regions, found in cases but not in controls (642 cases and 91 controls). A number of promising regions were found (overall p-values of 7.19×10-5 for San ancestry and \\textless2.00×10-16 for African ancestry), including chromosomes 15q15 and 17q22, which are close to genomic regions previously implicated in TB. Promising immune-related susceptibility genes such as the GADD45A, OSM and B7-H5 genes are also harboured in the identified regions. CONCLUSION: Admixture mapping is feasible in the South African Coloured population and a number of novel TB susceptibility genomic regions were uncovered.","language":"eng","journal":"BMC genomics","author":[{"propositions":[],"lastnames":["Daya"],"firstnames":["Michelle"],"suffixes":[]},{"propositions":["van","der"],"lastnames":["Merwe"],"firstnames":["Lize"],"suffixes":[]},{"propositions":[],"lastnames":["Gignoux"],"firstnames":["Christopher","R."],"suffixes":[]},{"propositions":["van"],"lastnames":["Helden"],"firstnames":["Paul","D."],"suffixes":[]},{"propositions":[],"lastnames":["Möller"],"firstnames":["Marlo"],"suffixes":[]},{"propositions":[],"lastnames":["Hoal"],"firstnames":["Eileen","G."],"suffixes":[]}],"year":"2014","pmid":"25422094","pmcid":"PMC4256931","note":"00000 ","pages":"1021","bibtex":"@article{daya_using_2014,\n\ttitle = {Using multi-way admixture mapping to elucidate {TB} susceptibility in the {South} {African} {Coloured} population},\n\tvolume = {15},\n\tissn = {1471-2164},\n\tdoi = {10.1186/1471-2164-15-1021},\n\tabstract = {BACKGROUND: The admixed South African Coloured population is ideally suited to the discovery of tuberculosis susceptibility genetic variants and their probable ethnic origins, but previous attempts at finding such variants using genome-wide admixture mapping were hampered by the inaccuracy of local ancestry inference. In this study, we infer local ancestry using the novel algorithm implemented in RFMix, with the emphasis on identifying regions of excess San or Bantu ancestry, which we hypothesize may harbour TB susceptibility genes.\nRESULTS: Using simulated data, we demonstrate reasonable accuracy of local ancestry inference by RFMix, with a tendency towards miss-calling San ancestry as Bantu. Regions with either excess San ancestry or excess African (San or Bantu) ancestry are less likely to be affected by this bias, and we therefore proceeded to identify such regions, found in cases but not in controls (642 cases and 91 controls). A number of promising regions were found (overall p-values of 7.19×10-5 for San ancestry and {\\textless}2.00×10-16 for African ancestry), including chromosomes 15q15 and 17q22, which are close to genomic regions previously implicated in TB. 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