New Arabidopsis thaliana study
by Dominik Grimm at 2020-10-16 06:40:13.273494+00:00
Lardon et. al. published an highly interesting new study in Communications Biology about "The genetic framework of shoot regeneration in Arabidopsis comprises master regulators and conditional fine-tuning factors" (Link). The GWAS results can be found here: GWAS Results. Phenotypes are publicly available at AraPheno.
New Features Released
by Dominik Grimm at 2019-10-21 14:12:24.120998+00:00
We implemented some features, that have been requested by the community, including the download of allele and phenotype information from the Detailed SNP View. In addition, we deployed a variety of bug fixes and performance updates.
by Dominik Grimm at 2018-08-30 08:06:12.199291+00:00
easyGWAS will be offline on the 30th of August, 8 p.m. (CET) until the 31st of August 11 a.m. (CET) for maintenance and updates. We are sorry for the inconvenience.
Pristionchus pacificus data available for download
by Dominik Grimm at 2017-02-28 11:53:31.461082+00:00
Data for the study Genomic Profiles of Diversification and Genotype–Phenotype Association in Island Nematode Lineages (McGaughran et. al.) is now available for download in easyGWAS. GWAS can be found here. Genotype data can be downloaded here.
Maintenance & Updates
by Dominik Grimm at 2017-02-06 15:05:34.792887+00:00
easyGWAS will be offline for approximately 1h on the 16th of February, 7p.m. (CET) for maintenance and updates. We are sorry for the inconvenience.
by Dominik Grimm at 2016-09-29 21:03:21.243641+00:00
We enhanced our annotation pipeline to provide on the fly annotations from Variant Effect Predictor (VEP) via the Ensembl REST API. The information will be provided in the "Detailed SNP" view, e.g. if you click on a SNP in the Manhattan plot (Read More...).
by Dominik Grimm at 2016-12-19 08:26:33.834561+00:00
We are happy to announce that easyGWAS got published in The Plant Cell: http://www.plantcell.org/content/early/2016/12/16/tpc.16.00551.abstract.
New Arabidopsis thaliana Study
by Dominik Grimm at 2018-04-28 06:38:25.349963+00:00
Vasseur et. al. published an impressive new study in PNAS about " Adaptive diversification of growth allometry in the plant Arabidopsis thaliana" (Link). GWAS from this study have been performed with easyGWAS. The GWAS results can be found here: GWAS Results.
New Study Available!
by Dominik Grimm at 2016-11-21 20:29:35.356768+00:00
We added a new study from Seymour et. al. (2016, PNAS) to easyGWAS about the "genetic architecture of nonadditive inheritance in Arabidopsis thaliana hybrids", including 372 in silico F1 genotypes and 20 phenotypes (Publicly available GWAS).
by Dominik Grimm at 2016-09-20 19:25:18.713786+00:00
We just released easyGWAS 2.6.
by Dominik Grimm at 2016-03-23 09:52:59.739439+00:00
easyGWAS moved to a new and more powerful server at the ETH Zürich!
by Dominik Grimm at 2016-10-04 20:39:49.913784+00:00
We added a Representational State Transfer (REST) API to easyGWAS. This allows users to obtain information from easyGWAS in various forms, simply by using URLs. For example to access meta-information for the sample with id 6944: https://easygwas.ethz.ch/rest/sample/public/6944.json
by Dominik Grimm at 2016-01-07 15:03:55.513329+00:00
We released easyGWAS version 2.5. This version comes with many new features including a detailed and dynamic SNP view, comparison of computed GWAS with dynamic visualisations as well as the upload of custom gene annotation sets. We also improved the performance and fixed some bugs. Overview of new features..
by Dominik Grimm at 2015-04-28 15:06:00.330672+00:00
Our servers will be maintained between the 8th and 12th of May. During this time easyGWAS will not be accessible. We apologise for any inconveniences.
by Dominik Grimm at 2014-09-18 13:40:56.018998+00:00
We released easyGWAS 2.0. The new version comes with a completely new design and many new features. With easyGWAS 2.0 users can upload their own private Genotype data as well as private phenotype, covariate or gene annotation data. We completely redesigned and reimplemented our algorithms to provide more speed for even larger datasets. We added Logistic Regression and permutation based algorithms. Further, we added algorithms to perform meta-analysis and already computed GWAS. Users now can upload precomputed summary statistics from other GWAS and run meta-analysis on these summary statistics an/or combine it with other private and public GWAS from easyGWAS.
by Dominik Grimm at 2013-01-10 15:36:23.943157+00:00
We added some new functionalities to easyGWAS:
by Dominik Grimm at 2012-11-13 15:13:07.294914+00:00
A beta version of easyGWAS is now online. We integrated different datasets for the model organisms Arabidopsis thaliana and Drosophila melanogaster.
NEW BETA VERSION RELEASED
by Dominik Grimm at 2012-11-13 15:15:09.145856+00:00
We are proud to announce a new release of easyGWAS. You now can add covariates and other additional factors (e.g. principle components) to your experiments. Furthermore, download options for data and summary statistics are available supporting various formats (CSV, PLINK, HDF5).
by Dominik Grimm at 2012-11-13 15:13:24.400516+00:00
Statistics and histograms are now provided for phenotypes in the result and the individual phenotype view.