We are incredibly proud to present GAIA, our cloud software that is capable of analyzing metagenomics data from any microbial community (bacteria, viruses and eukaryotes), from any matrix (human, animal, agricultural and environmental).
Gaia is the first tool to automatically integrate all hierarchic levels of taxonomic classification (from kingdom to subspecies) with functional classification, obtaining results in just 12 hours. It is also the first tool to offer comparative metagenomics in real time. GAIA is aimed at researchers who want to get to grips with their own data, and indeed, due to its intuitive interface and ease of use, GAIA does not require any specialized training; any researcher who is not an expert in bioinformatics can use this software and easily evaluate the analysis of the results obtained.
Authors: A. Paytuví, E. Battista, F. Scippacercola, R. Aiese Cigliano, W. Sanseverino
Insitutions:
- Sequentia Biotech
Publication: BioRxiv
Date: October 2019
Full paper: https://www.biorxiv.org/content/10.1101/804690v1.full
Abstract:
Identifying the biological diversity of a microbial population is of fundamental importance due to its implications in industrial processes, environmental studies and clinical applications. Today, there is still an outstanding need to develop new, easy-to-use bioinformatics tools to analyze both amplicon and shotgun metagenomics, including both prokaryotic and eukaryotic organisms, with the highest accuracy and the lowest running time. With the aim of overcoming this need, we introduce GAIA, an online software solution that has been designed to provide users with the maximum information whether it be 16S, 18S, ITS, or shotgun analysis. GAIA is able to obtain a comprehensive and detailed overview at any taxonomic level of microbiomes of different origins: human (e.g. stomach or skin), agricultural and environmental (e.g. land, water or organic waste). By using recently published benchmark datasets from shotgun and 16S experiments we compared GAIA against several available pipelines. Our results show that for shotgun metagenomics, GAIA obtained the highest F-measures at species level above all tested pipelines (CLARK, Kraken, LMAT, BlastMegan, DiamondMegan and NBC). For 16S metagenomics, GAIA also obtained excellent F-measures comparable to QIIME at family level. The overall objective of GAIA is to provide both the academic and industrial sectors with an integrated metagenomics suite that will allow to perform metagenomics data analysis easily, quickly and affordably with the highest accuracy.
