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Microbiome

Test your microbiome analysis pipeline with PLuMA

Study of the microbiome and metagenomics are actively developing areas of research. In the meantime, analyzing microbiome data has become increasingly complex, with multiple tools required to be run sequentially. Running these so-called “pipelines” of tools can be challenging because of the diversity of coding languages and compatibility issues.   To overcome this problem, Trevor Cickovski and Giri Narasimhan from the Bioinformatics Research Group of the Florida International University have developed PLuMA, a Plugin-Based Microbiome Analysis lightweight back end pipeline that supports multiple dynamically loaded plugin extensions. Here, they describe their tool and its main features.   Plugin-Based Microbiome Analysis   If you are an algorithm developer who wants to prototype, test and debug a new pipeline stage in your …

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Towards standardized protocols for microbiome studies

The study of the microbiome – that is, the ensemble of microbial communities living inside us – has become a major application for high-throughput DNA sequencing. Functional changes in the composition of the gut microbiome have been implicated in multiple human diseases. Due to its complexity, the analysis of sequencing data from microbiome study typically involves a lot of different protocols and bioinformatics tools. From sample collection and DNA extraction to sequencing and computational analysis, technical errors and bias can occur at each step, rendering the uniformization of protocols a complex task. To this end, two consortia recently proposed to examine the sources of inter-laboratory variability in various aspects of microbiome data generation. This work was published in the last …

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Process 16S rRNA sequences with the sl1p tool

Advancing DNA sequencing technologies have encouraged a surge of microbiome studies. The microbiome, the set of microbes (bacteria, viruses, archaea) who live in a particular environmental niche, has been extensively studied, including in the context of human disease, changes in ecological environments, and progressive oxygen gradients in the deep sea. One of the most popular methods for these types of studies is the sequencing of segments of the 16S rRNA gene– a highly conserved gene among bacterial populations which allows researchers to identify the taxonomic diversity within a given bacterial niche. Drs. Whelan and Surette have recently come up with a new tool, sl1p, that helps automate the processing of 16S rRNA gene sequencing data and provides analyses which allow the …

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