Data integration in microbial genomics ... - Jacobs University

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62 4. MIMARKS and sequencing contextual data, but extends them with further experimental contextual data such as PCR primers and conditions, or target gene name. For clarity and ease of use, all items within the MIMARKS checklist are presented with a value syntax description, as well as a clear definition of the item. Whenever terms from a specific ontology are required as the value of an item, these terms can be readily found in the respective ontology browsers linked by URLs in the item definition. Although this version of the MIMARKS checklist does not contain unit specifications, we recommend all units to be chosen from and follow the International System of Units (SI) recommendations. In addition, we strongly urge the community to provide feedback regarding the best unit recommendations for given parameters. Unit standardization across data sets will be vital to facilitate comparative studies in future. An Excel version of the MIMARKS checklist is provided on the GSC web site (). The MIxS environmental packages Fourteen environmental packages provide a wealth of environmental and epidemiological contextual data fields for a complete description of sampling environments. The environmental packages can be combined with any of the GSC checklists (Table 4.1 and Supplementary Results 2). Researchers within The Human Microbiome Project [Turnbaugh et al., 2007] contributed the host-associated and all human packages. The Terragenome Consortium contributed sediment and soil packages. Finally, ICoMM, Microbial Inventory Research Across Diverse Aquatic Long Term Ecological Research Sites and the Max Planck Institute for Marine Microbiology contributed the water package. The MI- MARKS working group developed the remaining packages (air, microbial mat/biofilm, miscellaneous natural or artificial environment, plant-associated and wastewater/sludge). The package names describe high-level habitat terms in order to be exhaustive. The miscellaneous natural or artificial environment package contains a generic set of parameters, and is included for any other habitat that does not fall into the other thirteen categories. Whenever needed, multiple packages may be used for the description of the environment. Examples of MIMARKS-compliant data sets Several MIMARKS-compliant reports are included in Supplementary
4.5. The MIMARKS checklist 63 Results 3. These include a 16S rRNA gene survey from samples obtained in the North Atlantic, an 18S pyrosequencing tag study of anaerobic protists in a permanently anoxic basin of the North Sea, a pmoA survey from Negev Desert soils, a dsrAB survey of Gulf of Mexico sediments and a 16S pyrosequencing tag study of bacterial diversity in the western English Channel (SRA accession no. SRP001108). Adoption by major database and informatics resources Support for adoption of MIMARKS and the MIxS standard has spread rapidly. Authors of this paper include representatives from genome sequencing centers, maintainers of major resources, principal investigators of large- and small-scale sequencing projects, and individual investigators who have provided compliant data sets, showing the breadth of support for the standard within the community. In the past, the INSDC has issued a reserved ‘barcode’ keyword for the CBOL7. Following this model, the INSDC has recently recognized the GSC as an authority for the MIxS standard and issued the standard with official keywords within INSDC nucleotide sequence records [Benson et al., 2008]. This greatly facilitates automatic validation of the submitted contextual data and provides support for data sets compliant with previous versions by including the checklist version as a keyword. GenBank accepts MIxS metadata in tabular format using the sequin and tbl2asn submission tools, validates MIxS compliance, and reports the fields in the structured comment block. The EBI-ENA Webin submission system provides prepared web forms for the submission of MIxS compliant data; it presents all of the appropriate fields with descriptions, explanations and examples, and validates the data entered. One tool that can aid submitting contextual data is MetaBar [Hankeln et al., 2010], a spreadsheet and web-based software, designed to assist users in the consistent acquisition, electronic storage and submission of contextual data associated with their samples in compliance with the MIxS standard. The online tool CDinFusion (http://www.megx.net/cdinfusion) was created to facilitate the combination of contextual data with sequence data, and generation of submission-ready files. The next-generation Sequence Read Archive (SRA) collects and dis-
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Max Planck Institute for Marine Mic
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List of abbreviations BLAST Basic L
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Thesis abstract Deoxyribonucleic ac
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4.2 Introduction . . . . . . . . .
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2 1. Introduction syntax: data leve
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4 1. Introduction used to derive ne
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6 1. Introduction croorganisms thri
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10 1. Introduction marker genes hel
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Page 65 and 66: 4.2. Introduction 57 edge generatio
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Page 110 and 111: 102 BIBLIOGRAPHY [Beynon-Davies, 20
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112 BIBLIOGRAPHY [Ramette, 2007] Ra
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116 BIBLIOGRAPHY [Williamson et al.
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CHAPTER 9 ACKNOWLEDGEMENTS First, I
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