Metacomp – an accurate and quantitative comparative metagenomics in EDGE Bioinformatics

Advances in shotgun sequencing technologies are revolutionizing our understanding of microbiomes associated with various environments such as humans, marine, soil, air, and other by enabling in situ, culture-free genomic... [ view full abstract ]

Advances in shotgun sequencing technologies are revolutionizing our understanding of microbiomes associated with various environments such as humans, marine, soil, air, and other by enabling in situ, culture-free genomic characterization of microbial communities. A typical shotgun metagenomic experiment involves sequencing a random sample of DNA or RNA fragments from the pool of microbial genomes or transcriptomes in a biological sample and yields tens of millions of reads. Although complex and challenging to analyze, these reads usually used to identify and quantify microbial taxa and/or genes and their function so that ‘‘who’’ is there and what they are doing.

The real power of metagenomics comes from comparing data across samples, either within a study or across studies. While it is a powerful tool for characterizing the immense microbial diversity on Earth, a number of challenges standing in the way of ready comparisons across shotgun datasets, among which is the need for larger datasets and the complexity of comparative analyses.

In this work, we present Metacomp – an R-based package integrated with EDGE Bioinformatics, which enables metagenomics comparative analytics and visualization. Leveraging EDGE Bioinformatics platform capacity of data pre-processing, read taxonomy assignment, and readily available results from other (NCBI Sequence Read Archive) projects, Metacomp enables an interactive Graphical User Interface-based workflow for metagenome comparative analyses. Specifically, along with EDGE, it allows to improve the study design, simplify data access, standardize metadata, and to produce reproducible results enabling accurate comparative metagenomics.