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TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population
BACKGROUND: The application of a subset of single nucleotide polymorphisms, the tagSNPs, can be useful in capturing untyped SNPs information in a genomic region. TagSNP transferability from the HapMap dataset to admixed populations is of uncertain value due population structure, admixture, drift and...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2737315/ https://www.ncbi.nlm.nih.gov/pubmed/19682379 http://dx.doi.org/10.1186/1423-0127-16-73 |
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author | Lins, Tulio C Abreu, Breno S Pereira, Rinaldo W |
author_facet | Lins, Tulio C Abreu, Breno S Pereira, Rinaldo W |
author_sort | Lins, Tulio C |
collection | PubMed |
description | BACKGROUND: The application of a subset of single nucleotide polymorphisms, the tagSNPs, can be useful in capturing untyped SNPs information in a genomic region. TagSNP transferability from the HapMap dataset to admixed populations is of uncertain value due population structure, admixture, drift and recombination effects. In this work an empirical dataset from a Brazilian admixed sample was evaluated against the HapMap population to measure tagSNP transferability and the relative loss of variability prediction. METHODS: The transferability study was carried out using SNPs dispersed over four genomic regions: the PTPN22, HMGCR, VDR and CETP genes. Variability coverage and the prediction accuracy for tagSNPs in the selected genomic regions of HapMap phase II were computed using a prediction accuracy algorithm. Transferability of tagSNPs and relative loss of prediction were evaluated according to the difference between the Brazilian sample and the pooled and single HapMap population estimates. RESULTS: Each population presented different levels of prediction per gene. On average, the Brazilian (BRA) sample displayed a lower power of prediction when compared to HapMap and the pooled sample. There was a relative loss of prediction for BRA when using single HapMap populations, but a pooled HapMap dataset generated minor loss of variability prediction and lower standard deviations, except at the VDR locus at which loss was minor using CEU tagSNPs. CONCLUSION: Studies that involve tagSNP selection for an admixed population should not be generally correlated with any specific HapMap population and can be better represented with a pooled dataset in most cases. |
format | Text |
id | pubmed-2737315 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27373152009-09-04 TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population Lins, Tulio C Abreu, Breno S Pereira, Rinaldo W J Biomed Sci Research BACKGROUND: The application of a subset of single nucleotide polymorphisms, the tagSNPs, can be useful in capturing untyped SNPs information in a genomic region. TagSNP transferability from the HapMap dataset to admixed populations is of uncertain value due population structure, admixture, drift and recombination effects. In this work an empirical dataset from a Brazilian admixed sample was evaluated against the HapMap population to measure tagSNP transferability and the relative loss of variability prediction. METHODS: The transferability study was carried out using SNPs dispersed over four genomic regions: the PTPN22, HMGCR, VDR and CETP genes. Variability coverage and the prediction accuracy for tagSNPs in the selected genomic regions of HapMap phase II were computed using a prediction accuracy algorithm. Transferability of tagSNPs and relative loss of prediction were evaluated according to the difference between the Brazilian sample and the pooled and single HapMap population estimates. RESULTS: Each population presented different levels of prediction per gene. On average, the Brazilian (BRA) sample displayed a lower power of prediction when compared to HapMap and the pooled sample. There was a relative loss of prediction for BRA when using single HapMap populations, but a pooled HapMap dataset generated minor loss of variability prediction and lower standard deviations, except at the VDR locus at which loss was minor using CEU tagSNPs. CONCLUSION: Studies that involve tagSNP selection for an admixed population should not be generally correlated with any specific HapMap population and can be better represented with a pooled dataset in most cases. BioMed Central 2009-08-14 /pmc/articles/PMC2737315/ /pubmed/19682379 http://dx.doi.org/10.1186/1423-0127-16-73 Text en Copyright © 2009 Lins et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Lins, Tulio C Abreu, Breno S Pereira, Rinaldo W TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population |
title | TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population |
title_full | TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population |
title_fullStr | TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population |
title_full_unstemmed | TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population |
title_short | TagSNP transferability and relative loss of variability prediction from HapMap to an admixed population |
title_sort | tagsnp transferability and relative loss of variability prediction from hapmap to an admixed population |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2737315/ https://www.ncbi.nlm.nih.gov/pubmed/19682379 http://dx.doi.org/10.1186/1423-0127-16-73 |
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