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...
Gespeichert in:
| Veröffentlicht in: | Methods in ecology and evolution 2015-08, Vol.6 (8), p.925-929 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 929 |
|---|---|
| container_issue | 8 |
| container_start_page | 925 |
| container_title | Methods in ecology and evolution |
| container_volume | 6 |
| creator | Frichot, Eric François, Olivier O'Meara, Brian |
| description | 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. |
| doi_str_mv | 10.1111/2041-210X.12382 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_02004815v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3777290281</sourcerecordid><originalsourceid>FETCH-LOGICAL-c6342-da0fa7ae255cd28d46bf730626761fa2166798badd3cece2c8de782749c236053</originalsourceid><addsrcrecordid>eNqFkcFLwzAUxosoOObOXgNe9NAteWmT1lsd1QkVQRS8hSxNZ2fX1GZV9t-bWhniQd8lj8fv-3gvn-edEjwlrmaAA-IDwc9TAjSCA2-0nxz-6I-9ibVr7IpGMYZg5F1laXKJkho9oEaqV7nSqDAtqmSdWyUbjVyDtDKVWZVKVkhaa1Qpt6Wpkd12eantiXdUyMrqyfc79p6u08f5ws_ub27nSeYrRgPwc4kLyaWGMFQ5RHnAlgWnmAHjjBQSCGM8jpYyz6nSSoOKcs0j4EGsgDIc0rF3Mfi-yEo0bbmR7U4YWYpFkol-hgHjICLhO3Hs-cA2rXnrtN2KTWmVrtxd2nRWEI5jEgMNwaFnv9C16draXSKA8gAwDVn8F-W83G9GnPRes4FSrbG21cV-T4JFH5TooxB9FOIrKKdgg-KjrPTuP1zcpSkdhJ8VlJB8</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1703898712</pqid></control><display><type>article</type><title>LEA: An R package for landscape and ecological association studies</title><source>Wiley Online Library Journals Frontfile Complete</source><source>Alma/SFX Local Collection</source><creator>Frichot, Eric ; François, Olivier ; O'Meara, Brian</creator><creatorcontrib>Frichot, Eric ; François, Olivier ; O'Meara, Brian</creatorcontrib><description>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.</description><identifier>ISSN: 2041-210X</identifier><identifier>EISSN: 2041-210X</identifier><identifier>DOI: 10.1111/2041-210X.12382</identifier><language>eng</language><publisher>London: John Wiley & Sons, Inc</publisher><subject>Alleles ; control of false discoveries ; Datasets ; Ecological association ; ecological association studies ; Ecological effects ; 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</subject><ispartof>Methods in ecology and evolution, 2015-08, Vol.6 (8), p.925-929</ispartof><rights>2015 The Authors. Methods in Ecology and Evolution © 2015 British Ecological Society</rights><rights>Copyright © 2015 British Ecological Society</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c6342-da0fa7ae255cd28d46bf730626761fa2166798badd3cece2c8de782749c236053</citedby><cites>FETCH-LOGICAL-c6342-da0fa7ae255cd28d46bf730626761fa2166798badd3cece2c8de782749c236053</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2F2041-210X.12382$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2F2041-210X.12382$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://hal.science/hal-02004815$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Frichot, Eric</creatorcontrib><creatorcontrib>François, Olivier</creatorcontrib><creatorcontrib>O'Meara, Brian</creatorcontrib><title>LEA: An R package for landscape and ecological association studies</title><title>Methods in ecology and evolution</title><description>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.</description><subject>Alleles</subject><subject>control of false discoveries</subject><subject>Datasets</subject><subject>Ecological association</subject><subject>ecological association studies</subject><subject>Ecological effects</subject><subject>Environmental conditions</subject><subject>Gene frequency</subject><subject>Genetics</subject><subject>genome scans for signature of local adaptation</subject><subject>Genomes</subject><subject>Genotype & phenotype</subject><subject>inference of population structure</subject><subject>Life Sciences</subject><subject>Natural selection</subject><subject>Polymorphism</subject><subject>Population genetics</subject><subject>Population structure</subject><subject>Population studies</subject><subject>Populations and Evolution</subject><subject>Statistical analysis</subject><issn>2041-210X</issn><issn>2041-210X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqFkcFLwzAUxosoOObOXgNe9NAteWmT1lsd1QkVQRS8hSxNZ2fX1GZV9t-bWhniQd8lj8fv-3gvn-edEjwlrmaAA-IDwc9TAjSCA2-0nxz-6I-9ibVr7IpGMYZg5F1laXKJkho9oEaqV7nSqDAtqmSdWyUbjVyDtDKVWZVKVkhaa1Qpt6Wpkd12eantiXdUyMrqyfc79p6u08f5ws_ub27nSeYrRgPwc4kLyaWGMFQ5RHnAlgWnmAHjjBQSCGM8jpYyz6nSSoOKcs0j4EGsgDIc0rF3Mfi-yEo0bbmR7U4YWYpFkol-hgHjICLhO3Hs-cA2rXnrtN2KTWmVrtxd2nRWEI5jEgMNwaFnv9C16draXSKA8gAwDVn8F-W83G9GnPRes4FSrbG21cV-T4JFH5TooxB9FOIrKKdgg-KjrPTuP1zcpSkdhJ8VlJB8</recordid><startdate>201508</startdate><enddate>201508</enddate><creator>Frichot, Eric</creator><creator>François, Olivier</creator><creator>O'Meara, Brian</creator><general>John Wiley & Sons, Inc</general><general>Wiley</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7SN</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>1XC</scope></search><sort><creationdate>201508</creationdate><title>LEA: An R package for landscape and ecological association studies</title><author>Frichot, Eric ; François, Olivier ; O'Meara, Brian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c6342-da0fa7ae255cd28d46bf730626761fa2166798badd3cece2c8de782749c236053</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Alleles</topic><topic>control of false discoveries</topic><topic>Datasets</topic><topic>Ecological association</topic><topic>ecological association studies</topic><topic>Ecological effects</topic><topic>Environmental conditions</topic><topic>Gene frequency</topic><topic>Genetics</topic><topic>genome scans for signature of local adaptation</topic><topic>Genomes</topic><topic>Genotype & phenotype</topic><topic>inference of population structure</topic><topic>Life Sciences</topic><topic>Natural selection</topic><topic>Polymorphism</topic><topic>Population genetics</topic><topic>Population structure</topic><topic>Population studies</topic><topic>Populations and Evolution</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Frichot, Eric</creatorcontrib><creatorcontrib>François, Olivier</creatorcontrib><creatorcontrib>O'Meara, Brian</creatorcontrib><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Ecology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Methods in ecology and evolution</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Frichot, Eric</au><au>François, Olivier</au><au>O'Meara, Brian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>LEA: An R package for landscape and ecological association studies</atitle><jtitle>Methods in ecology and evolution</jtitle><date>2015-08</date><risdate>2015</risdate><volume>6</volume><issue>8</issue><spage>925</spage><epage>929</epage><pages>925-929</pages><issn>2041-210X</issn><eissn>2041-210X</eissn><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.</abstract><cop>London</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1111/2041-210X.12382</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2041-210X |
| ispartof | Methods in ecology and evolution, 2015-08, Vol.6 (8), p.925-929 |
| issn | 2041-210X 2041-210X |
| language | eng |
| recordid | cdi_hal_primary_oai_HAL_hal_02004815v1 |
| source | Wiley Online Library Journals Frontfile Complete; Alma/SFX Local Collection |
| subjects | Alleles control of false discoveries Datasets Ecological association ecological association studies Ecological effects 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 |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T22%3A58%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=LEA:%20An%20R%20package%20for%20landscape%20and%20ecological%20association%20studies&rft.jtitle=Methods%20in%20ecology%20and%20evolution&rft.au=Frichot,%20Eric&rft.date=2015-08&rft.volume=6&rft.issue=8&rft.spage=925&rft.epage=929&rft.pages=925-929&rft.issn=2041-210X&rft.eissn=2041-210X&rft_id=info:doi/10.1111/2041-210X.12382&rft_dat=%3Cproquest_hal_p%3E3777290281%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1703898712&rft_id=info:pmid/&rfr_iscdi=true |