Sampling Properties of Estimators of Nucleotide Diversity at Discovered snp Sites

• Autorzy: Renwick A. , Bonnen P. E. , Trikka D. , Nelson D. L. , Chakraborty R. , Kimmel M.
• Języki publikacji: EN

Abstrakty

EN

SNP sites are generally discovered by sequencing regions of the human genome in a limited number of individuals. This may leave SNP sites present in the region, but containing rare mutant nucleotides, undetected. Consequently, estimates of nucleotide diversity obtained from assays of detected SNP sites are biased. In this research we present a statistical model of the SNP discovery process, which is used to evaluate the extent of this bias. This model involves the symmetric Beta distribution of variant frequencies at SNP sites, with an additional probability that there is no SNP at any given site. Under this model of allele frequency distributions at SNP sites, we show that nucleotide diversity is always underestimated. However, the extent of bias does not seem to exceed 10-15% for the analyzed data. We find that our model of allele frequency distributions at SNP sites is consistent with SNP statistics derived based on new SNP data at ATM, BLM, RQL and WRN gene regions. The application of the theory to these new SNP data as well as to the literature data at the LPL gene region indicates that in spite of ascertainment biases, the observed differences of nucleotide diversity across these gene regions are real. This provides interesting evidence concerning the heterogeneity of the rates of nucleotide substitution across the genome.

Słowa kluczowe

EN

single nucleotide polymorphisms; ascertainment bias; nucleotide diversity; molecular evolution

PL

pojedyncze nukleotydowe polymorfizmy; błąd potwierdzający; ewolucja molekularna

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2003
• Tom: Vol. 13, no 3
• Strony: 385--394
• Opis fizyczny: Bibliogr. 13 poz., tab., wykr.

Twórcy

autor

Renwick A.

• Department of Statistics, Rice University, 6100 Main Street, Mail Stop 138, Houston, TX 77005, USA

autor

Bonnen P. E.

• Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA

autor

Trikka D.

• Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA

autor

Nelson D. L.

• Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA

autor

Chakraborty R.

• Center for Genome Information, University of Cincinnati, Cincinnati, OH, USA

autor

Kimmel M.

• Department of Statistics, Rice University, 6100 Main Street, Mail Stop 138, Houston, TX 77005, USA

Bibliografia

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