LEA: An R package for landscape and ecological association studies

Summary Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant statistical association with ecological gradients. Ecological association studies can provide lists of genetic polymorphisms that are pot...

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Vydané v:Methods in ecology and evolution Ročník 6; číslo 8; s. 925 - 929
Hlavní autori: Frichot, Eric, François, Olivier, O'Meara, Brian
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London John Wiley & Sons, Inc 01.08.2015
Wiley
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ISSN:2041-210X, 2041-210X
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Abstract Summary Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant statistical association with ecological gradients. Ecological association studies can provide lists of genetic polymorphisms that are potentially involved in local adaptation to environmental conditions through natural selection. Here, we present the R package LEA that enables users to run ecological association studies from the R command line. The package can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. It derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results. This note also illustrates the main steps of ecological association studies and the typical use of LEA for analysing data sets based on R commands.
AbstractList Summary Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant statistical association with ecological gradients. Ecological association studies can provide lists of genetic polymorphisms that are potentially involved in local adaptation to environmental conditions through natural selection. Here, we present the R package LEA that enables users to run ecological association studies from the R command line. The package can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. It derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results. This note also illustrates the main steps of ecological association studies and the typical use of LEA for analysing data sets based on R commands.
Summary Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant statistical association with ecological gradients. Ecological association studies can provide lists of genetic polymorphisms that are potentially involved in local adaptation to environmental conditions through natural selection. Here, we present the R package LEA that enables users to run ecological association studies from the R command line. The package can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. It derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results. This note also illustrates the main steps of ecological association studies and the typical use of LEA for analysing data sets based on R commands.
Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant statistical association with ecological gradients. Ecological association studies can provide lists of genetic polymorphisms that are potentially involved in local adaptation to environmental conditions through natural selection.Here, we present the R package LEA that enables users to run ecological association studies from the R command line. The package can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. It derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results.This note also illustrates the main steps of ecological association studies and the typical use of LEA for analysing data sets based on R commands.
1. Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant statistical association with ecological gradients. Ecological association studies can provide lists of genetic polymorphisms that are potentially involved in local adaptation to environmental conditions through natural selection. 2. Here, we present the R package LEA that enables users to run ecological association studies from the R command line. The package can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. It derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results. 3. This note also illustrates the main steps of ecological association studies and the typical use of LEA for analysing data sets based on R commands.
Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant statistical association with ecological gradients. Ecological association studies can provide lists of genetic polymorphisms that are potentially involved in local adaptation to environmental conditions through natural selection. Here, we present the R package LEA that enables users to run ecological association studies from the R command line. The package can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. It derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results. This note also illustrates the main steps of ecological association studies and the typical use of LEA for analysing data sets based on R commands.
Author Frichot, Eric
O'Meara, Brian
François, Olivier
Author_xml – sequence: 1
  givenname: Eric
  surname: Frichot
  fullname: Frichot, Eric
  organization: TIMC‐IMAG UMR 5525
– sequence: 2
  givenname: Olivier
  surname: François
  fullname: François, Olivier
  organization: TIMC‐IMAG UMR 5525
– sequence: 3
  givenname: Brian
  surname: O'Meara
  fullname: O'Meara, Brian
BackLink https://hal.science/hal-02004815$$DView record in HAL
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Snippet Summary Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit...
Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant...
Summary Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit...
1. Based on population genomic and environmental data, genomewide ecological association studies aim at detecting allele frequencies that exhibit significant...
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SubjectTerms Alleles
control of false discoveries
Datasets
Ecological association
ecological association studies
Ecological effects
Ecological studies
Environmental conditions
Gene frequency
Genetics
genome scans for signature of local adaptation
Genomes
Genotype & phenotype
inference of population structure
Life Sciences
Natural selection
Polymorphism
Population genetics
Population structure
Population studies
Populations and Evolution
Statistical analysis
Title LEA: An R package for landscape and ecological association studies
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