Data

University of Tasmania, Australia
Dorothy Steane ; Peter Harrison
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://data.utas.edu.au/metadata/07c9dad2-cdbb-46f8-8c99-c8fc517bfdf5&rft.title=๐˜ˆ๐˜ณ๐˜ต๐˜ฉ๐˜ณ๐˜ฐ๐˜ฑ๐˜ฐ๐˜ฅ๐˜ช๐˜ถ๐˜ฎ ๐˜ง๐˜ช๐˜ฎ๐˜ฃ๐˜ณ๐˜ช๐˜ข๐˜ต๐˜ถ๐˜ฎ genomics datasets&rft.identifier=https://data.utas.edu.au/metadata/07c9dad2-cdbb-46f8-8c99-c8fc517bfdf5&rft.publisher=University of Tasmania, Australia&rft.description=Final filtered SNP datasets used in the study by Jordan ๐˜ฆ๐˜ต ๐˜ข๐˜ญ. 2023 titled Landscape genomics reveals signals of climate adaptation and a cryptic lineage in ๐˜ˆ๐˜ณ๐˜ต๐˜ฉ๐˜ณ๐˜ฐ๐˜ฑ๐˜ฐ๐˜ฅ๐˜ช๐˜ถ๐˜ฎ ๐˜ง๐˜ช๐˜ฎ๐˜ฃ๐˜ณ๐˜ช๐˜ข๐˜ต๐˜ถ๐˜ฎ (citation below). The dataset comprise SNP genotypes for 13 provenance and 10 provenances. Each file can be read into R using the 'readRDS()' function. This will read in a list object that contains 5 datasets used for analysis. This includes a (i) 'genlight' object of class adegenet, (ii) 'genmat' object of class matrix (row = sample, column = SNP) that was used to create the genind object, (iii) 'genind' object of class adegenet, (iv) 'genpop' object of class adegenet, and (v) 'allele_freq' object of class matrix comprising the population allele frequencies (row = sample, column = SNP).&rft.creator=Dorothy Steane &rft.creator=Peter Harrison &rft.date=2023&rft.relation=UTAS/publications/155997&rft_rights=Attribution - NonCommercial(BY - NC) http://creativecommons.org/licenses/by-nc/4.0/&rft_subject=Biological adaptation&rft_subject=Evolutionary biology&rft_subject=BIOLOGICAL SCIENCES&rft_subject=Ecological impacts of climate change and ecological adaptation&rft_subject=Climate change impacts and adaptation&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Conservation and biodiversity&rft_subject=Environmental management&rft_subject=Environmental rehabilitation and restoration&rft_subject=Rehabilitation or conservation of terrestrial environments&rft_subject=Terrestrial systems and management&rft_subject=ENVIRONMENTAL MANAGEMENT&rft_subject=Ecosystem adaptation to climate change&rft_subject=Adaptation to climate change&rft_subject=ENVIRONMENTAL POLICY, CLIMATE CHANGE AND NATURAL HAZARDS&rft_subject=DArTSeq&rft_subject=climate adaptation&rft_subject=restoration&rft_subject=SNP&rft.type=dataset&rft.language=English Access the data

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http://creativecommons.org/licenses/by-nc/4.0/

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Final filtered SNP datasets used in the study by Jordan ๐˜ฆ๐˜ต ๐˜ข๐˜ญ. 2023 titled "Landscape genomics reveals signals of climate adaptation and a cryptic lineage in ๐˜ˆ๐˜ณ๐˜ต๐˜ฉ๐˜ณ๐˜ฐ๐˜ฑ๐˜ฐ๐˜ฅ๐˜ช๐˜ถ๐˜ฎ ๐˜ง๐˜ช๐˜ฎ๐˜ฃ๐˜ณ๐˜ช๐˜ข๐˜ต๐˜ถ๐˜ฎ" (citation below). The dataset comprise SNP genotypes for 13 provenance and 10 provenances. Each file can be read into R using the 'readRDS()' function. This will read in a list object that contains 5 datasets used for analysis. This includes a (i) 'genlight' object of class adegenet, (ii) 'genmat' object of class matrix (row = sample, column = SNP) that was used to create the genind object, (iii) 'genind' object of class adegenet, (iv) 'genpop' object of class adegenet, and (v) 'allele_freq' object of class matrix comprising the population allele frequencies (row = sample, column = SNP).

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ACN 633 798 857