Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium

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Standard

Correcting for ascertainment biases when analyzing SNP data : applications to the estimation of linkage disequilibrium. / Nielsen, Rasmus; Signorovitch, James.

In: Theoretical Population Biology, Vol. 63, No. 3, 2003, p. 245-255.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Nielsen, R & Signorovitch, J 2003, 'Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium', Theoretical Population Biology, vol. 63, no. 3, pp. 245-255. https://doi.org/10.1016/S0040-5809(03)00005-4

APA

Nielsen, R., & Signorovitch, J. (2003). Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium. Theoretical Population Biology, 63(3), 245-255. https://doi.org/10.1016/S0040-5809(03)00005-4

Vancouver

Nielsen R, Signorovitch J. Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium. Theoretical Population Biology. 2003;63(3):245-255. https://doi.org/10.1016/S0040-5809(03)00005-4

Author

Nielsen, Rasmus ; Signorovitch, James. / Correcting for ascertainment biases when analyzing SNP data : applications to the estimation of linkage disequilibrium. In: Theoretical Population Biology. 2003 ; Vol. 63, No. 3. pp. 245-255.

Bibtex

@article{77d95b3b8056420e92881143053e0094,
title = "Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium",
abstract = "As large-scale sequencing efforts turn from single genome sequencing to polymorphism discovery, single nucleotide polymorphisms (SNPs) are becoming an increasingly important class of population genetic data. But because of the ascertainment biases introduced by many methods of SNP discovery, most SNP data cannot be analyzed using classical population genetic methods. Statistical methods must instead be developed that can explicitly take into account each method of SNP discovery. Here we review some of the current methods for analyzing SNPs and derive sampling distributions for single SNPs and pairs of SNPs for some common SNP discovery schemes. We also show that the ascertainment scheme has a large effect on the estimation of linkage disequilibrium and recombination, and describe some methods of correcting for ascertainment biases when estimating recombination rates from SNP data.",
author = "Rasmus Nielsen and James Signorovitch",
year = "2003",
doi = "10.1016/S0040-5809(03)00005-4",
language = "English",
volume = "63",
pages = "245--255",
journal = "Theoretical Population Biology",
issn = "0040-5809",
publisher = "Academic Press",
number = "3",

}

RIS

TY - JOUR

T1 - Correcting for ascertainment biases when analyzing SNP data

T2 - applications to the estimation of linkage disequilibrium

AU - Nielsen, Rasmus

AU - Signorovitch, James

PY - 2003

Y1 - 2003

N2 - As large-scale sequencing efforts turn from single genome sequencing to polymorphism discovery, single nucleotide polymorphisms (SNPs) are becoming an increasingly important class of population genetic data. But because of the ascertainment biases introduced by many methods of SNP discovery, most SNP data cannot be analyzed using classical population genetic methods. Statistical methods must instead be developed that can explicitly take into account each method of SNP discovery. Here we review some of the current methods for analyzing SNPs and derive sampling distributions for single SNPs and pairs of SNPs for some common SNP discovery schemes. We also show that the ascertainment scheme has a large effect on the estimation of linkage disequilibrium and recombination, and describe some methods of correcting for ascertainment biases when estimating recombination rates from SNP data.

AB - As large-scale sequencing efforts turn from single genome sequencing to polymorphism discovery, single nucleotide polymorphisms (SNPs) are becoming an increasingly important class of population genetic data. But because of the ascertainment biases introduced by many methods of SNP discovery, most SNP data cannot be analyzed using classical population genetic methods. Statistical methods must instead be developed that can explicitly take into account each method of SNP discovery. Here we review some of the current methods for analyzing SNPs and derive sampling distributions for single SNPs and pairs of SNPs for some common SNP discovery schemes. We also show that the ascertainment scheme has a large effect on the estimation of linkage disequilibrium and recombination, and describe some methods of correcting for ascertainment biases when estimating recombination rates from SNP data.

U2 - 10.1016/S0040-5809(03)00005-4

DO - 10.1016/S0040-5809(03)00005-4

M3 - Journal article

C2 - 12689795

AN - SCOPUS:0042991419

VL - 63

SP - 245

EP - 255

JO - Theoretical Population Biology

JF - Theoretical Population Biology

SN - 0040-5809

IS - 3

ER -

ID: 222644701