Supporting data for "Gigwa v2 – Extended and improved genotype investigator"

Dataset type: Metadata, Genomic, Software, Transcriptomic
Data released on April 05, 2019

Sempéré G; Pétel A; Rouard M; Frouin J; Hueber Y; De Bellis F; Larmande P (2019): Supporting data for "Gigwa v2 – Extended and improved genotype investigator" GigaScience Database. http://dx.doi.org/10.5524/100585

DOI10.5524/100585

The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of NGS technologies lead to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution.
Gigwa v2 is an easy to use, species-agnostic web application for managing and exploring high density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various standalone or online tools. It implements two standard RESTful APIs, GA4GH, which is healthoriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third party applications. The project home page http://www.southgreen.fr/content/gigwa provides a list of live instances allowing to test the system on public data (or reasonably-sized user-provided data).
This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its userfriendliness and interoperability make it widely accessible to the life science community.

Additional details

Read the peer-reviewed publication(s):

(PubMed: 31077313)

Related datasets:

doi:10.5524/100585 IsNewVersionOf doi:10.5524/100199

Additional information:

http://www.southgreen.fr/content/gigwa

https://github.com/SouthGreenPlatform/Gigwa2





File NameSample IDData TypeFile FormatSizeRelease Date 
Sequence variantsVCF93.85 MB2019-04-03
Sequence variantsVCF124.68 MB2019-04-03
Sequence variantsVCF12.83 MB2019-04-03
Sequence variantsVCF1.41 GB2019-04-03
Sequence variantsVCF25.55 MB2019-04-03
ScriptGZIP115.91 KB2019-04-04
GitHub archivearchive1.68 MB2019-03-22
ReadmeTEXT3.51 KB2019-04-04
Displaying 1-8 of 8 File(s).
Date Action
April 5, 2019 Dataset publish
April 23, 2019 Manuscript Link added : 10.1093/gigascience/giz051
October 14, 2022 Manuscript Link updated : 10.1093/gigascience/giz051