Center for Computational and Theoretical Biology
Refine
Has Fulltext
- yes (47)
Is part of the Bibliography
- yes (47)
Year of publication
Document Type
- Journal article (40)
- Doctoral Thesis (6)
- Preprint (1)
Keywords
- machine learning (5)
- active zone (4)
- Caenorhabditis elegans (2)
- bee decline (2)
- dSTORM (2)
- deep learning (2)
- evolution (2)
- foraging (2)
- genetic architecture (2)
- juvenile hormone (2)
Institute
- Center for Computational and Theoretical Biology (47)
- Theodor-Boveri-Institut für Biowissenschaften (20)
- Pathologisches Institut (4)
- Physiologisches Institut (4)
- Julius-von-Sachs-Institut für Biowissenschaften (3)
- Klinik und Poliklinik für Unfall-, Hand-, Plastische und Wiederherstellungschirurgie (Chirurgische Klinik II) (3)
- Neurochirurgische Klinik und Poliklinik (3)
- Urologische Klinik und Poliklinik (3)
- Comprehensive Cancer Center Mainfranken (2)
- Klinik und Poliklinik für Dermatologie, Venerologie und Allergologie (2)
EU-Project number / Contract (GA) number
- 2020010013 (1)
- 250194-Carnivorom (1)
- 835102) (1)
The abundance of high-quality genotype and phenotype data for the model organism Arabidopsis thaliana enables scientists to study the genetic architecture of many complex traits at an unprecedented level of detail using genome-wide association studies (GWAS). GWAS have been a great success in A. thaliana and many SNP-trait associations have been published. With the AraGWAS Catalog (https://aragwas.1001genomes.org) we provide a publicly available, manually curated and standardized GWAS catalog for all publicly available phenotypes from the central A. thaliana phenotype repository, AraPheno. All GWAS have been recomputed on the latest imputed genotype release of the 1001 Genomes Consortium using a standardized GWAS pipeline to ensure comparability between results. The catalog includes currently 167 phenotypes and more than 222 000 SNP-trait associations with P < 10\(^{-4}\), of which 3887 are significantly associated using permutation-based thresholds. The AraGWAS Catalog can be accessed via a modern web-interface and provides various features to easily access, download and visualize the results and summary statistics across GWAS.