The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Estimation of allele frequency and association mapping using next-generation sequencing data
Open accessAbstract
BACKGROUND: Estimation of allele frequency is of fundamental importance in population genetic analyses and in association mapping. In most studies using next-generation sequencing, a cost effective approach is to use medium or low-coverage data (e.g., < 15X). However, SNP calling and allele frequency estimation in such studies is associated with substantial statistical uncertainty because of varying coverage and high error rates. RESULTS: We evaluate a new maximum likelihood method for estimating allele frequencies in low and medium coverage next-generation sequencing data. The method is based on integrating over uncertainty in the data for each individual rather than first calling genotypes. This method can be applied to directly test for associations in case/control studies. We use simulations to compare the likelihood method to methods based on genotype calling, and show that the likelihood method outperforms the genotype calling methods in terms of: (1) accuracy of allele frequency estimation, (2) accuracy of the estimation of the distribution of allele frequencies across neutrally evolving sites, and (3) statistical power in association mapping studies. Using real re-sequencing data from 200 individuals obtained from an exon-capture experiment, we show that the patterns observed in the simulations are also found in real data. CONCLUSIONS: Overall, our results suggest that association mapping and estimation of allele frequencies should not be based on genotype calling in low to medium coverage data. Furthermore, if genotype calling methods are used, it is usually better not to filter genotypes based on the call confidence score.
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Cites
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“The “Inflation” factor [44] is shown in the upper left corner of each figure.”
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Cited by
ANGSD: Analysis of Next Generation Sequencing Data
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Self-citationEstimating Individual Admixture Proportions from Next Generation Sequencing Data
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Self-citationInferring Population Structure and Admixture Proportions in Low-Depth NGS Data
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Self-citationRAD Capture (Rapture): Flexible and Efficient Sequence-Based Genotyping
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“The latter method is based on the likelihood function described in [11,22,23,29].”
BackgroundMethodSelf-citation
Metadata
- Authors
- Kim, S. Y., Lohmueller, K. E., Albrechtsen, A., Li, Y., Korneliussen, T., Tian, G., Grarup, N., Jiang, T., Andersen, G., Witte, D., Jorgensen, T., Hansen, T., Pedersen, O., Wang, J., & Nielsen, R.
- Venue
- BMC Bioinformatics
- Published
- 2011-06-11
- Volume
- 12
- Issue
- 1
- Pages
- 231-231
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W2148181482
- Cited by
- 217
- References
- 12
- FWCI
- 5.05
- Type
- journal article
- Language
- en
- Open access
- gold
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- Kim, S. Y., Lohmueller, K. E., Albrechtsen, A., Li, Y., Korneliussen, T., Tian, G., Grarup, N., Jiang, T., Andersen, G., Witte, D., Jorgensen, T., Hansen, T., Pedersen, O., Wang, J., & Nielsen, R. (2011). Estimation of allele frequency and association mapping using next-generation sequencing data. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-12-231
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