Data from: Successful by chance? the power of mixed models and neutral simulations for the detection of individual fixed hete

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关键词：

Demography;Life history: ecology;Modeling: individual based;Methods: computer simulations;Fitness;Chionomys nivalis

DOI：

doi:10.5061/dryad.3cb61

摘要：

iled to detect fixed heterogeneity, thus challenging previous results from mixed models (MM). To understand the causes of this discrepancy, we estimate

Data from: Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations

负责人：

Muchadeyi, Farai C.

关键词：

Goats production systems landscape genomics Spatial Analysis Method Latent Factor Mixed Models RDA adaptive loci environments

DOI：

doi:10.5061/dryad.3402n

摘要：

(1.75%) SNPs, while Latent Factor Mixed Models identified 714 (1.48%) SNPs significantly associated with environmental variables. Significant markers wer

Data from: Effects of gene action, marker density, and time since selection on the performance of landscape genomic scans of local adaptation

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关键词：

Antagonistic pleiotropy;standing variation Subject area: Genomics and gene mapping;genotype-environment association;selective sweeps;conditional neutrality;linkage disequilibrium

DOI：

doi:10.5061/dryad.p12q4

摘要：

analyses (linear models, mixed linear models, and latent factor mixed models) and an implementation of BayEnv all performed well, with high rates of true

Data from: Landscape permeability and individual variation in a dispersal-linked gene jointly determine genetic structure in the Glanville fritilla

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关键词：

gene flow;Life History Evolution;Genetic Variation;Melitaea cinxia;polymorphism

DOI：

doi:10.5061/dryad.mp25s15

摘要：

factor mixed models to identify the landscape features that best predict spatial sorting of alleles in the dispersal-related gene phosphoglucose isomerase

Data from: Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes

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关键词：

CDPOP;natural selection;latent factor mixed model;ordination methods;complex landscapes;genome scans

DOI：

doi:10.5061/dryad.v0c77

摘要：

differences across GEA methods based on levels of population structure. The univariate GEA approach had high FPRs (up to 55%) under limited dispersal scenarios

Data from: Local adaptation (mostly) remains local: reassessing environmental associations of climate-related candidate SNPs in Arabidopsis halleri

负责人：

关键词：

landscape genomics;local adaptation;candidate genes;environmental association analysis;natural selection.;Arabidopsis halleri

DOI：

doi:10.5061/dryad.h9022

摘要：

s with the same methodology (partial Mantel tests, PMTs) as in the original study and additionally with a latent factor mixed model (LFMM) approach. Of the 74