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  AraPheno: a public database for Arabidopsis thaliana phenotypes

Seren, U., Grimm, D., Fitz, J., Weigel, D., Nordborg, M., Borgwardt, K., et al. (2017). AraPheno: a public database for Arabidopsis thaliana phenotypes. Nucleic Acids Research, 45(D1), D1054-D1059. doi:10.1093/nar/gkw986.

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 Creators:
Seren, Uemit1, Author
Grimm, Dominik2, Author
Fitz, Joffrey3, Author
Weigel, Detlef3, Author
Nordborg, Magnus1, Author
Borgwardt, Karsten2, Author
Korte, Arthur4, Author
Affiliations:
1Gregor Mendel Institute of Molecular Plant Biology, Vienna, ou_persistent22              
2Machine Learning and Computational Biology Lab, Department of Biosystems Science and Engineering, ETH Zürich, ou_persistent22              
3Max Planck Institute for Developmental Biology, Max Planck Society, Max-Planck-Ring 5, 72076 Tübingen, DE, ou_2421691              
4enter for Computational and Theoretical Biology, University Würzburg, ou_persistent22              

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Free keywords: GENOME-WIDE ASSOCIATION; MIXED-MODEL APPROACH; STRUCTURED POPULATIONS; GENETIC-VARIATION; TRAITS; PLANT
 Abstract: Natural genetic variation makes it possible to discover evolutionary changes that have been maintained in a population because they are advantageous. To understand genotype-phenotype relationships and to investigate trait architecture, the existence of both high-resolution genotypic and phenotypic data is necessary. Arabidopsis thaliana is a prime model for these purposes. This herb naturally occurs across much of the Eurasian continent and North America. Thus, it is exposed to a wide range of environmental factors and has been subject to natural selection under distinct conditions. Full genome sequencing data for more than 1000 different natural inbred lines are available, and this has encouraged the distributed generation of many types of phenotypic data. To leverage these data for meta analyses, AraPheno (https://arapheno.1001genomes.org) provide a central repository of population-scale phenotypes for A. thaliana inbred lines. AraPheno includes various features to easily access, download and visualize the phenotypic data. This will facilitate a comparative analysis of the many different types of phenotypic data, which is the base to further enhance our understanding of the genotype-phenotype map.

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Language(s): eng - English
 Dates: 2016-08-152016-10-182016-10-242017-01-04
 Publication Status: Issued
 Pages: 6
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: 000396575500145
DOI: 10.1093/nar/gkw986
 Degree: -

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Title: Nucleic Acids Research
  Other : Nucleic Acids Res.
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 45 (D1) Sequence Number: - Start / End Page: D1054 - D1059 Identifier: ISSN: 0301-5610
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000262810