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      Microbiome Helper: a Custom and Streamlined Workflow for Microbiome Research

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          Abstract

          As the microbiome field continues to grow, a multitude of researchers are learning how to conduct proper microbiome experiments. We outline here a streamlined and custom approach to processing samples from detailed sequencing library construction to step-by-step bioinformatic standard operating procedures. This allows for rapid and reliable microbiome analysis, allowing researchers to focus more on their experiment design and results. Our sequencing protocols, bioinformatic tutorials, and bundled software are freely available through Microbiome Helper. As the microbiome research field continues to evolve, Microbiome Helper will be updated with new protocols, scripts, and training materials.

          ABSTRACT

          Sequence-based approaches to study microbiomes, such as 16S rRNA gene sequencing and metagenomics, are uncovering associations between microbial taxa and a myriad of factors. A drawback of these approaches is that the necessary sequencing library preparation and bioinformatic analyses are complicated and continuously changing, which can be a barrier for researchers new to the field. We present three essential components to conducting a microbiome experiment from start to finish: first, a simplified and step-by-step custom gene sequencing protocol that requires limited lab equipment, is cost-effective, and has been thoroughly tested and utilized on various sample types; second, a series of scripts to integrate various commonly used bioinformatic tools that is available as a standalone installation or as a single downloadable virtual image; and third, a set of bioinformatic workflows and tutorials to provide step-by-step guidance and education for those new to the microbiome field. This resource will provide the foundations for those newly entering the microbiome field and will provide much-needed guidance and best practices to ensure that quality microbiome research is undertaken. All protocols, scripts, workflows, tutorials, and virtual images are freely available through the Microbiome Helper website ( https://github.com/mlangill/microbiome_helper/wiki).

          IMPORTANCE As the microbiome field continues to grow, a multitude of researchers are learning how to conduct proper microbiome experiments. We outline here a streamlined and custom approach to processing samples from detailed sequencing library construction to step-by-step bioinformatic standard operating procedures. This allows for rapid and reliable microbiome analysis, allowing researchers to focus more on their experiment design and results. Our sequencing protocols, bioinformatic tutorials, and bundled software are freely available through Microbiome Helper. As the microbiome research field continues to evolve, Microbiome Helper will be updated with new protocols, scripts, and training materials.

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          Most cited references40

          • Record: found
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          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              QIIME allows analysis of high-throughput community sequencing data.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                mSystems
                mSystems
                msys
                msys
                mSystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                3 January 2017
                Jan-Feb 2017
                : 2
                : 1
                : e00127-16
                Affiliations
                CGEB-Integrated Microbiome Resource (IMR) and Department of Pharmacology, Dalhousie University, Halifax, Canada
                UC Davis Genome Center
                Author notes
                Address correspondence to Morgan G. I. Langille, morgan.g.i.langille@ 123456dal.ca .

                Citation Comeau AM, Douglas GM, Langille MGI. 2017. Microbiome Helper: a custom and streamlined workflow for microbiome research. mSystems 2:e00127-16. https://doi.org/10.1128/mSystems.00127-16.

                Article
                mSystems00127-16
                10.1128/mSystems.00127-16
                5209531
                28066818
                1aa9633c-8668-46ae-ad0a-252bacc67b4c
                Copyright © 2017 Comeau et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 13 September 2016
                : 8 December 2016
                Page count
                supplementary-material: 2, Figures: 5, Tables: 2, Equations: 0, References: 49, Pages: 11, Words: 7108
                Funding
                Funded by: Dalhousie University Strategic Research Initiatives Fund
                Award Recipient : Morgan G. I. Langille
                Categories
                Methods and Protocols
                Novel Systems Biology Techniques
                Custom metadata
                January/February 2017

                16s rrna gene sequencing,microbiome helper,bioinformatics,dual-indexing pcr,education,metagenomics,microbiome,standard operating procedure,virtual machine

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