Gigwa-Genotype investigator for genome-wide analyses.

Guilhem Sempéré,Gautier Sarah,Alexis Dereeper,Manuel Ruiz,Florian Philippe,Pierre Larmande

doi:10.1186/s13742-016-0131-8

Abstract

BackgroundExploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions.DescriptionHere we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats.ConclusionsThe Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-016-0131-8) contains supplementary material, which is available to authorized users.

Highlights

HBV is one of the smallest enveloped DNA viruses and the prototype member of the family Hepadnaviridae
This analysis highlighted two miRNAs that have previously been associated with breast cancer but for which we provide some insights on the molecular mechanisms underlying their dysregulation
We address the high dimensionality of transcriptomic data, i.e. the ”large p, small n” problem, by generating the matrix ⇥ over the temporal modes obtained by the proper orthogonal decomposition (POD) [10]

Summary

Introduction

There have been many pan-genomics studies performed on microorganisms (Vernikos et al, 2015) In plants, this approach has been recently carried on wild and cultivated African rice species to investigate the e↵ects of domestication on pan-genome structure (Monat et al, 2018). Quantitative metagenomics is broadly employed to identify genera or species associated with several diseases These data are obtained by mapping the reads of each sample against operational taxonomic units (OTU) or a gene catalog. The e↵ects and roles of DNA repeats on the maturation of fleshy fruits, which is a complex process of key agro-economic interest, still needs to be investigated comprehensively and tomato is arguably an excellent model for such study. ProteoRE is built upon the Galaxy web-based technology, a scientific workflow system allowing for data integration, data and analysis persistence and providing interfaces for users to interact with tools dedicated to the functional and the visual analysis of proteomics datasets

Objectives

Methods

Results

Discussion

Conclusion