Abstract
Metagenomic sequencing is an increasingly common tool in environmental and biomedical sciences yet analysis workflows remain immature relative to other field such as DNASeq and RNASeq analysis pipelines. While software for detailing the composition of microbial communities using 16S rRNA marker genes is constantly improving, increasingly researchers are interested in identifying changes exhibited within microbial communities under differing environmental conditions. In order to gain maximum value from metagenomic sequence data we must improve the existing analysis environment by providing accessible and scalable computational workflows able to generate reproducible results. Here we describe a complete end-to-end open-source metagenomics workflow running within Galaxy for 16S differential abundance analysis. The workflow accepts 454 or Illumina sequence data (either overlapping or non-overlapping paired end reads) and outputs lists of the operational taxonomic unit (OTUs) exhibiting the greatest change under differing conditions. A range of analysis steps and graphing options are available giving users a high-level of control over their data and analyses. Additionally, users are able to input complex sample-specific metadata information which can be incorporated into differential analysis and used for grouping / colouring within graphs. Detailed tutorials containing sample data and existing workflows are available for three different input types: overlapping and non-overlapping read pairs as well as for pre-generated Biological Observation Matrix (BIOM) files. Using the Galaxy platform we developed MetaDEGalaxy, a complete metagenomics differential abundance analysis workflow. MetaDEGalaxy is designed for bench scientists working with 16S data who are interested in comparative metagenomics. MetaDEGalaxy builds on momentum within the wider Galaxy metagenomics community with the hope that more tools will be added as existing methods mature.
Highlights
It is recognized that there is a strong link between microbial communities in the human body and human health[1]
Using the Galaxy platform we developed MetaDEGalaxy, a complete metagenomics differential abundance analysis workflow
Uncovering how the composition and function of the micro-biome impacts human health represents a significant area of growth
Summary
It is recognized that there is a strong link between microbial communities in the human body and human health[1]. While the importance of such communities is understood, the composition and function of the human micro-biome largely remains a mystery. Uncovering how the composition and function of the micro-biome impacts human health represents a significant area of growth. Another important area of research growth is the study of environmental microbial communities in fields such as agriculture, marine science, and ecology. By identifying the composition of microbial communities, researchers are able to link microbes to specific environments and using comparative metagenomics identify how microbial communities’ changes under altered environmental conditions. Central to elucidating the link between the metagenomic data and human health or altered environmental conditions is sequencing; obtaining useful research outcomes from large volumes of unprocessed sequence data represents a challenge for many bench scientists. The major bottleneck in obtaining value from such data is the huge computational and logistic task required for analysing the large volumes of sequencing data routinely generated in a single sequencing run
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