Demographic history and rare allele sharing among human populations

By Simon Gravel, B. Henn, Ryan N. Gutenkunst, Amit R. Indap, Gabor T. Marth, Andrew G. Clark, F. Yu, Richard A. Gibbs, Carlos D. Bustamante. Proceedings of the National Academy of Sciences of the United States of America, 2011

660 citations recorded by the source corpus.

Subfields: Genetics

View Paper: https://www.semanticscholar.org/paper/ffddba9b5ca80db44e0eaa82b59345e5c0286afe

How researchers see this paper

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

In Genetics

Citations in the corpus

Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics (2013, methodology): “7 Neutral simulations of a complex demographic model To estimate the number of rare variants expected under neutrality, we used MaCS (62) to simulate 100 neutral collections of 1,354 regions (size range 10-10,373 bp, matching the number and size range of the ultrasensitive regions) in 911 individual”
Linkage disequilibrium dependent architecture of human complex traits reveals action of negative selection (2016, methodology): “We used demographical model parameters estimated in Gravel et al.(27) to simulate European and African human genetic data, and assumed a generation time of 25 years.”
When Is Selection Effective? (2014, methodology): “This model begins with an ancestral population of size Nr = 11930 with frequency distribution following the quasi-stationary distribution of Kimura [29], and features population splits and size changes that were inferred from synonymous polymorphism from the 1000 Genomes dataset [30].”
ANGSD: Analysis of Next Generation Sequencing Data (2014, background): “This is also observed between Chinese and Africans [28] and the difference between the SNP chip data and the sequencing data is caused by ascertainment biases in the chip data where SNPs are often chosen because they are common in populations such as European [27].”
Repetitive DNA and next-generation sequencing: computational challenges and solutions (2011, background): “Genome resequencing allows researchers to study genetic variation by analysing many genomes from the same or from closely related species 23,35–37 .”
Quantifying unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects (2016, positive): “Leveraging this connection, previous methods used Bayesian and jackknife approaches to estimate the discovery rate of new variants 4,5,15 .”
Estimating Mutation Load in Human Genomes (2015, positive): “For example, Gravel et al.(57) considered the probability that”
Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program (2019, background): “The relative numbers of singletons, doubletons and other very rare variants can be used to infer human demographic history 11,55,56 .”
Robust Demographic Inference from Genomic and SNP Data (2013, methodology): “…SFS, we have chosen here to incorporate the bias in the model and to infer demographic parameters directly from the ascertained (joint) SFS, a strategy similar in spirit to that used by Gravel et al. [28] to account for biases in the SFS obtained from low-coverage next-generation sequencing data.”
Genome-Wide Inference of Ancestral Recombination Graphs (2013, background): “ee below). Since the coalescent process is Markovian in time, the distribution for the vector of branch counts can be factored 21 by time intervals, P(C jN)=P(C 0) K Õ l=1 P(C l jC l 1;Ds l 1;N l 1); (14) with degenerate ﬁrst and last terms, P(C 0)=I[C 0 =n] and P(C K jC K 1;N K 1)=I[C K =1]. The co”
SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data (2012, neutral): “[35] provided an alternative approach.”
Inferring human population size and separation history from multiple genome sequences (2014, positive): “…ancestors that we observe reconciles the timing of the most recent common ancestor of African and Non-African mtDNA around 70kya [1, 18] with the lower autosomal nuclear mutation rate used here, which in simple split models would suggest a separation around 90-130kya [7, 17, 33, 41, 46].”