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ISA-Tab Standards at Metabolomics Society Meeting, Tsuruoka 2014, Japan

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Introducing ISA-Tab Format, key features, patterns, curation issues, supporting software and RDF conversion

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ISA-Tab Standards at Metabolomics Society Meeting, Tsuruoka 2014, Japan

  1. 1. ISA-Tab as a COSMOS standard Metabolomics Data Standards and Capture Workshop Metabolomics Society Meeting 2014, Tsuruoka, Japan Philippe Rocca-Serra (PhD) University of Oxford e-Research Centre
  2. 2. Data exchange, Let information flow! • Tenets of Science: reproducibility of results and findings • justifies the right to access data • publishing a manuscript is no longer enough • data should be published and released along side • A GEO or an ArrayExpress for Metabolomic Data • What would you do if you had access to 25000 studies in Metabolomics today?
  3. 3. Data Provenance and Preservation It is all about structuring experimental information to make it available to computer and software agents to enable: Notes in Lab Books (information for humans) Spreadsheets and Tables ( the compromise) Facts as RDF statements (information for machines)
  4. 4. Exchange as Main Goal • Exchange of experimental description: the Study Plan • description of subjects and perturbations: ISA-TAB • Exchange of spectral acquisition file: the Raw Data • enables review, assessment,appraisal, reuse: MzML,nmrML • Exchange of findings: the Results and Interpretation • identified metabolites: Mz-TAB and Metabolite Annotation File
  5. 5. The essential value of Contextual Data or Metadata • “Data about the Data” –description of the data (descriptive metadata) • Lazy way: “it is all in the file name” approach CNL_MOA1_C2_LD_TP1_EWR.cdf • Is this enough to understand what this experiment is about ....5 years from now?
  6. 6. ISA-Tab format in a nutshell (1) ISA metadata specifications: •workflow and process orientated •compatible with checklist enforcement •compatible with external vocabulary resources •compatible by design with existing schemas
  7. 7. • Investigation File: cardinality: 1..1 –purpose: think “executive summary” – layout: rows of key value pairs organized in blocks – content: • Why? general study description • How? methods / protocol declaration • How? variable declarations (predictor and response variables) • Who? contact and affiliation information • Study File: cardinality: 1..n –layout: true header/row of record table (think “sorting, filtering of samples”) –content: • What? Listing all biological materials collected over the study course and their treatments. • Assay File: cardinality: 1..n –layout: true header/row of record table (think “sorting, filtering of datafiles”) –content: • What? Listing all data acquisition events and data files collected by a given assay and subsequent data transformations ISA-Tab format in a nutshell (II)
  8. 8. ISA syntax: Characteristics[<tag>] Declaring and annotating an ISA Source Name or Sample Name ISA syntax: Protocol REF with sets of Parameter Value[<tag>] resulting in a ISA node Sample Name Worked example-ISA Study Sample File: Describing Study Subjects and their features ISA syntax: Factor Value[<tag>] for reporting treatments or study groups as a set of levels of independent variables
  9. 9. Worked example - ISA Assay File: reporting signal acquisition events ISA Pattern for LC-MS: Splitting in 2 distinct assay tables, one per scan polarity ISA Pattern for GC-MS: Report derivatization as an extra sample prep step ISA Pattern for NMR:
  10. 10. • Different kinds of experiments, Different annotation needs • CIMR ISA configurations to deal with Biological Specifics • Clinical Context (Human as subjects) • Non-clinical Context (=Animal as subjects) • Plant Context (=Plants as subjects) • In-vitro Context ( = Cell as subject) Dealing with Diversity: ISA configurations for ISAcreator
  11. 11. 30/06/2013 12 In-vitro study Plant study Clinical study https://github.com/ISA-tools/Configuration-Files Dealing with Diversity: Refining CIMR ISA configurations
  12. 12. Dealing with Diversity: Refining CIMR ISA configurations • Different kinds of experiments, Different annotation needs • additional ISA assay table definitions to deal with technology needs • Targeted profiling or global metabolomics analysis • liquid chromatography mass spectrometry • gas chromatography mass spectrometry • direct infusion mass spectrometry • 1D /2D NMR spectroscopy • Metabolic Flux Analysis (ongoing work with Pr Marta Cascante)
  13. 13. Developed to be a user friendly way to enter standards-compliant metadata: it has lots of features... But these are just some of them...we also have a data entry wizard and an import utility... The ISAcreator: an editor for ISA-Tab format https://github.com/ISA-tools/ISAcreator
  14. 14. The ISAcreator: an editor for ISA-Tab format https://github.com/ISA-tools/ISAcreator
  15. 15. ISAcreator features: visualizing experimental workflows Work completed during investigation of new approach for creation of glyphs with use of taxonomy for guidance. See Maguire et al, Taxonomy-Based Glyph Design – with a Case Study on Visualizing Workflows of Biological Experiments, IEEE Transactions on Visualization and Computer Graphics, 2012
  16. 16. This bit of code indicates you need to invoke ISA configuration which define expected table layout in order to proceed ISAcreator features: API https://github.com/ISA-tools/ISAcreator/wiki/API
  17. 17. https://github.com/ISA-tools/Risa
  18. 18. ISAViewer: ISA-Tab viewing component on the web https://github.com/ISA-tools/ISATab-Viewer
  19. 19. ISA patterns for reporting QC samples Annotation Rule of Thumb: does the reported value satisfy the ‘is_a’ rule? In this representation, QC1 would be interpreted to be an instance of organism whose type is a ‘vanillic acid’ => incorrect Improved representation: QC1 would be interpreted to be an instance of chemical compound whose type is a ‘vanillic acid’ => incorrect acting as ‘positive control’ Furthermore, only 2 actual study subject will be accounted for
  20. 20. Why does it matter? It is all about structuring experimental information to make it available to computer and software agents to enable: Notes in Lab Books (information for humans) Spreadsheets and Tables ( the compromise) Facts as RDF statements (information for machines)
  21. 21. RDF representation of Metabolomics Experimental information • Query Expansion and Data Discovery https://github.com/ISA-tools/isa2owl
  22. 22. RDF representation of Metabolomic Experimental information • Conversion of 80 % of public datasets • Tests against case-queries report partial success • Points to the need to enforce stricter curation rules in order to fully benefit from the RDF representation • Existing conversion already enables easy cohort creation • Ongoing work: converting MAF file to RDF • enabling querying from experimental metadata to chemical identities and vice-versa. https://github.com/ISA-tools/isa2owl
  23. 23. Contributing to Metabolights and ISA • BBRSC UK-China Award & BGI funded Hackathon • venue: BGI Hong-Kong • Participants: • Metabolights/BGI/ISA/Birmingham/Hong- Kong University • Outcome: • ISAtab web viewer code • Functional Specifications & Code for DoE Wisard API
  24. 24. Contributing to Metabolights and ISA • BBRSC UK-China Award funded Hackathon will be back! • 2nd Meeting to be organised • Fancy participating? get in touch! • isatools@googlegroups.com
  25. 25. Don’t miss out • 2 Main Publishers involved in developing Data Journals • (Scott Edmunds (GigaScience) and Susanna Sansone (NPG Scientific Data) • Representatives from Metabolomics Repository • Get all the help you need for depositing your data and increase the visibility of your research!
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  27. 27. Questions?? You can email us... isatools@googlegroups.com View our blog http://isatools.wordpress.com Follow us on Twitter @isatools View our website http://www.isa-tools.org Thanks for listening... View our Git repo & contribute http://github.com/ISA-tools

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