Your browser doesn't support javascript.
loading
Unbiased Estimation of Linkage Disequilibrium from Unphased Data.
Ragsdale, Aaron P; Gravel, Simon.
Afiliación
  • Ragsdale AP; Department of Human Genetics, McGill University, Montreal, QC, Canada.
  • Gravel S; Department of Human Genetics, McGill University, Montreal, QC, Canada.
Mol Biol Evol ; 37(3): 923-932, 2020 03 01.
Article en En | MEDLINE | ID: mdl-31697386
ABSTRACT
Linkage disequilibrium (LD) is used to infer evolutionary history, to identify genomic regions under selection, and to dissect the relationship between genotype and phenotype. In each case, we require accurate estimates of LD statistics from sequencing data. Unphased data present a challenge because multilocus haplotypes cannot be inferred exactly. Widely used estimators for the common statistics r2 and D2 exhibit large and variable upward biases that complicate interpretation and comparison across cohorts. Here, we show how to find unbiased estimators for a wide range of two-locus statistics, including D2, for both single and multiple randomly mating populations. These unbiased statistics are particularly well suited to estimate effective population sizes from unlinked loci in small populations. We develop a simple inference pipeline and use it to refine estimates of recent effective population sizes of the threatened Channel Island Fox populations.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biología Computacional / Zorros Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Mol Biol Evol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2020 Tipo del documento: Article País de afiliación: Canadá

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biología Computacional / Zorros Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Mol Biol Evol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2020 Tipo del documento: Article País de afiliación: Canadá
...