Hitchhiking under positive Darwinian selection.

By Justin C. Fay, Chung-I Wu. Genetics, 2000

1,803 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4d959fce6817d2eb7a60b8568bbe52235854ca3b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Population Genomics: Whole-Genome Analysis of Polymorphism and Divergence in Drosophila simulans (2007, methodology): “To address this possibility, we calculated Fay and Wu’s H [56] for 10-kb windows across the genome using only sites with a coverage of five alleles and windows not located in extended regions of reduced heterozygosity near the distal and proximal ends of chromosome arms (Materials and Methods).”
Search for nucleotide diversity patterns of local adaptation in dehydrins and other cold-related candidate genes in Scots pine (Pinus sylvestris L.) (2008, methodology): “Deviations of particular genes from the frequency distribution spectrum under standard neutral model of evolution were assessed with Tajima’s D (Tajima 1989), Fay and Wu H ( Fay and Wu 2000 ), and Ramos–Onsins and Rozas R2 tests (Ramos-Onsins and Rozas 2002).”
Positive and negative selection on the human genome. (2001, background): “While many more high frequency SNPs would be needed to show a significant increase in the A/S ratio, analysis of flanking variation for a hitchhiking effect would provide direct evidence for positive selection (Fay and Wu 2000).”
Assessment of the Genetic Diversity in Forest Tree Populations Using Molecular Markers (2014, methodology): “’s E [69–72] and the McDonald–Kreitman and HKA (Hudson-Kreitman-Aguade) tests [73,74],”
Mapping signatures of positive selection in the genome of livestock (2014, background): “Fay and Wu H test (Fay and Wu, 2000), uses an out-group sequence to infer the ancestral allele at each polymorphic site and tests specifically for an excess of high-frequency non-ancestral alleles.”
Detecting a local signature of genetic hitchhiking along a recombining chromosome. (2002, methodology): “…gene of moderate length. ing event produces an excess of rare alleles (Braverman However, the large variance of nucleotide diversity in a et al. 1995; Fu 1997) and high-frequency-derived alleles DNA sample makes it difficult to distinguish the pattern (Fay and Wu 2000) in a sample of DNA sequences.”
Detecting loci under selection in a hierarchically structured population (2009, unknown): “Several procedures have been proposed to detect loci under selection based on the patterns of genetic diversity found in a population (Tajima, 1989; Fu, 1997; Fay and Wu, 2000; Kim and Stephan, 2002; Sabeti et al., 2002; Nielsen et al., 2005; Voight et al., 2006; Zeng et al., 2006).”
DnaSP, DNA polymorphism analyses by the coalescent and other methods (2003, methodology): “(2) Depaulis and Veuille's haplotype-based tests (Depaulis and Veuille, 1998); (3) B-and Q-tests (Wall, 1999); (4) H -test (Fay and Wu, 2000); (5) Z nS , ZZ and Z A linkage disequilibrium based-statistics (Kelly, 1997; Rozas et al., 2001).”
Supervised Machine Learning for Population Genetics: A New Paradigm (2018, methodology): “…strength to population genetics analysis: while inferences are traditionally based on a single summary statistic devised for the given task (e.g., [34–40]), below we describe several recent studies which demonstrate that far greater statistical power can be achieved by simultaneously examining…”
Not so different after all: a comparison of methods for detecting amino acid sites under selection. (2005, background): “…demographic history of the population, unlike many ‘‘neutrality tests’’ (Tajima 1989, 1996; Fu and Li 1993 a , 1993 b ; Deng and Fu 1996; Fu 1997; Misawa and Tajima 1997; Fay and Wu 2000), which compare estimates of effective population size obtained using different measures of genetic variation.”