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      PIPITS: an automated pipeline for analyses of fungal internal transcribed spacer sequences from the Illumina sequencing platform

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          Summary

          1. Studying fungal biodiversity using data generated from Illumina Mi Seq sequencing platforms poses a number of bioinformatic challenges with the analysis typically involving a large number of tools for each analytical step from quality filtering to generating identified operational taxonomic unit ( OTU) abundance tables.

          2. Here, we introduce PIPITS, an open‐source stand‐alone suite of software for automated processing of Illumina Mi Seq sequences for fungal community analysis. PIPITS exploits a number of state of the art applications to process paired‐end reads from quality filtering to producing OTU abundance tables.

          3. We provide detailed descriptions of the pipeline and show its utility in the analysis of 9 396 092 sequences generated on the Mi Seq platform from Illumina Mi Seq.

          4. PIPITS is the first automated bioinformatics pipeline dedicated for fungal ITS sequences which incorporates ITSx to extract subregions of ITS and exploits the latest RDP Classifier to classify sequences against the curated UNITE fungal data set.

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          The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis

          J. R. Cole, B. Chai, R. J. Farris … (2004)
          The Ribosomal Database Project (RDP-II) provides the research community with aligned and annotated rRNA gene sequences, along with analysis services and a phylogenetically consistent taxonomic framework for these data. Updated monthly, these services are made available through the RDP-II website (http://rdp.cme.msu.edu/). RDP-II release 9.21 (August 2004) contains 101 632 bacterial small subunit rRNA gene sequences in aligned and annotated format. High-throughput tools for initial taxonomic placement, identification of related sequences, probe and primer testing, data navigation and subalignment download are provided. The RDP-II email address for questions or comments is rdpstaff@msu.edu.
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            Current state and perspectives of fungal DNA barcoding and rapid identification procedures.

            Wolfgang Maier, R Nilsson, Martin Unterseher … (2010)
            Fungal research is experiencing a new wave of methodological improvements that most probably will boost mycology as profoundly as molecular phylogeny has done during the last 15 years. Especially the next generation sequencing technologies can be expected to have a tremendous effect on fungal biodiversity and ecology research. In order to realise the full potential of these exciting techniques by accelerating biodiversity assessments, identification procedures of fungi need to be adapted to the emerging demands of modern large-scale ecological studies. But how should fungal species be identified in the near future? While the answer might seem trivial to most microbiologists, taxonomists working with fungi may have other views. In the present review, we will analyse the state of the art of the so-called barcoding initiatives in the light of fungi, and we will seek to evaluate emerging trends in the field. We will furthermore demonstrate that the usability of DNA barcoding as a major tool for identification of fungi largely depends on the development of high-quality sequence databases that are thoroughly curated by taxonomists and systematists.
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              CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

              Samuel V. Angiuoli, Malcolm Matalka, Aaron Gussman … (2011)
              Background Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. Results We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. Conclusion The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Methods Ecol Evol
                Journal ID (iso-abbrev): Methods Ecol Evol
                Journal ID (doi): 10.1111/(ISSN)2041-210X
                Journal ID (publisher-id): MEE3
                Title: Methods in Ecology and Evolution
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Electronic): 2041-210X
                Publication date (Electronic): 25 May 2015
                Publication date (Print): August 2015
                Volume: 6
                Issue: 8 ( doiID: 10.1111/mee3.2015.6.issue-8 )
                Pages: 973-980
                Affiliations
                [ 1 ]Centre for Ecology & Hydrology Maclean Building Benson Lane Crowmarsh Gifford Wallingford, Oxon OX10 8BBUK
                [ 2 ]Royal Botanic Garden Edinburgh 20A Inverleith Row Edinburgh EH3 5LRUK
                Author notes
                [*] [* ]Correspondence author. E‐mail: hyugwe@ 123456ceh.ac.uk .
                Article
                Publisher ID: MEE312399
                DOI: 10.1111/2041-210X.12399
                PMC ID: 4981123
                PubMed ID: 27570615
                SO-VID: 492b588d-b804-4732-9232-d0d10d0e3ee3
                Copyright © © 2015 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
                License:

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 13 March 2015
                Date accepted : 16 April 2015
                Page count
                Pages: 8
                Funding
                Funded by: NERC NBAF‐W
                Funded by: Tree Health and Plant Biosecurity Initiative project ProTree
                Award ID: BB/L012243/1
                Funded by: NERC as a Daphne Jackson Trust Fellow at RBGE
                Funded by: European Commission project, EcoFINDERS
                Award ID: FP7‐264465
                Categories
                Subject: Application
                Subject: Fungal Genetics
                Custom metadata
                source-schema-version-number 2.0
                component-id mee312399
                cover-date August 2015
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_NLMPMC version:4.9.4 mode:remove_FC converted:10.08.2016

                Keywords: bioinformatics,dna metabarcoding,fungi,internal transcribed spacer,pipeline
                Data availability:
                Keywords: bioinformatics, dna metabarcoding, fungi, internal transcribed spacer, pipeline

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