Dataset Information

MetaBar - a tool for consistent contextual data acquisition and standards compliant submission.

ABSTRACT: BACKGROUND: Environmental sequence datasets are increasing at an exponential rate; however, the vast majority of them lack appropriate descriptors like sampling location, time and depth/altitude: generally referred to as metadata or contextual data. The consistent capture and structured submission of these data is crucial for integrated data analysis and ecosystems modeling. The application MetaBar has been developed, to support consistent contextual data acquisition. RESULTS: MetaBar is a spreadsheet and web-based software tool designed to assist users in the consistent acquisition, electronic storage, and submission of contextual data associated to their samples. A preconfigured Microsoft Excel spreadsheet is used to initiate structured contextual data storage in the field or laboratory. Each sample is given a unique identifier and at any stage the sheets can be uploaded to the MetaBar database server. To label samples, identifiers can be printed as barcodes. An intuitive web interface provides quick access to the contextual data in the MetaBar database as well as user and project management capabilities. Export functions facilitate contextual and sequence data submission to the International Nucleotide Sequence Database Collaboration (INSDC), comprising of the DNA DataBase of Japan (DDBJ), the European Molecular Biology Laboratory database (EMBL) and GenBank. MetaBar requests and stores contextual data in compliance to the Genomic Standards Consortium specifications. The MetaBar open source code base for local installation is available under the GNU General Public License version 3 (GNU GPL3). CONCLUSION: The MetaBar software supports the typical workflow from data acquisition and field-sampling to contextual data enriched sequence submission to an INSDC database. The integration with the megx.net marine Ecological Genomics database and portal facilitates georeferenced data integration and metadata-based comparisons of sampling sites as well as interactive data visualization. The ample export functionalities and the INSDC submission support enable exchange of data across disciplines and safeguarding contextual data.

SUBMITTER: Hankeln W

PROVIDER: S-EPMC2912304 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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MetaBar - a tool for consistent contextual data acquisition and standards compliant submission.

Hankeln Wolfgang W Buttigieg Pier Luigi PL Fink Dennis D Kottmann Renzo R Yilmaz Pelin P Glöckner Frank Oliver FO

BMC bioinformatics 20100630

<h4>Background</h4>Environmental sequence datasets are increasing at an exponential rate; however, the vast majority of them lack appropriate descriptors like sampling location, time and depth/altitude: generally referred to as metadata or contextual data. The consistent capture and structured submission of these data is crucial for integrated data analysis and ecosystems modeling. The application MetaBar has been developed, to support consistent contextual data acquisition.<h4>Results</h4>MetaB ...[more]

PMID: 20591175

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Project description:Accurate knowledge of retention time (RT) in liquid chromatography-based mass spectrometry data facilitates peptide identification, quantification, and multiplexing in targeted and discovery-based workflows. Retention time prediction is particularly important for peptide analysis in emerging data-independent acquisition (DIA) experiments such as SWATH-MS. The indexed RT approach, iRT, uses synthetic spiked-in peptide standards (SiRT) to set RT to a unit-less scale, allowing for normalization of peptide RT between different samples and chromatographic set-ups. The obligatory use of SiRTs can be costly and complicates comparisons and data integration if standards are not included in every sample. Reliance on SiRTs also prevents the inclusion of archived mass spectrometry data for generation of the peptide assay libraries central to targeted DIA-MS data analysis. We have identified a set of peptide sequences that are conserved across most eukaryotic species, termed Common internal Retention Time standards (CiRT). In a series of tests to support the appropriateness of the CiRT-based method, we show: (1) the CiRT peptides normalized RT in human, yeast, and mouse cell lysate derived peptide assay libraries and enabled merging of archived libraries for expanded DIA-MS quantitative applications; (2) CiRTs predicted RT in SWATH-MS data within a 2-min margin of error for the majority of peptides; and (3) normalization of RT using the CiRT peptides enabled the accurate SWATH-MS-based quantification of 340 synthetic isotopically labeled peptides that were spiked into either human or yeast cell lysate. To automate and facilitate the use of these CiRT peptide lists or other custom user-defined internal RT reference peptides in DIA workflows, an algorithm was designed to automatically select a high-quality subset of datapoints for robust linear alignment of RT for use. Implementations of this algorithm are available for the OpenSWATH and Skyline platforms. Thus, CiRT peptides can be used alone or as a complement to SiRTs for RT normalization across peptide spectral libraries and in quantitative DIA-MS studies.

Dataset Information

MetaBar - a tool for consistent contextual data acquisition and standards compliant submission.

Publications

MetaBar - a tool for consistent contextual data acquisition and standards compliant submission.

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