Abstract
BackgroundThe dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, non-specialists are faced with the double challenge of choosing among an ever-increasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches.ResultsHere we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi’o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment.ConclusionsAltogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and well-documented commands.
Highlights
The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities
The advent of high-throughput sequencing technologies in 2008 made it possible to directly sequence the different microbial genomes present in a given sample as well as measuring the expression profiles of those genomes in a culture-independent manner. This supposed a revolution in the field of microbial ecology, as it allowed to profile the taxonomic composition and functional potential of microbial communities [1] and eventually to recover full genomes from environmental bacteria that in some cases could not be studied by other means [2]
We use anvi’o to visually explore subsets of the metagenomes, as well as the bins obtained by the SqueezeMeta pipeline
Summary
The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. The advent of high-throughput sequencing technologies in 2008 made it possible to directly sequence the different microbial genomes present in a given sample (metagenomics) as well as measuring the expression profiles of those genomes (metatranscriptomics) in a culture-independent manner This supposed a revolution in the field of microbial ecology, as it allowed to profile the taxonomic composition and functional potential of microbial communities [1] and eventually to recover full genomes from environmental bacteria that in some cases could not be studied by other means [2]. There is a need for tools that allow life science researchers to reliably analyse meta’omics data with minimal training Such tools should provide interfaces that relieve users from the burden of processing large amounts of data, while still giving them enough freedom to pose and answer biologically meaningful questions
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