Database Integration to Improve Accessibility to Public High-throughput Sequencing Data

Transcript

1. Database Integration to Improve Accessibility to High-Throughput Seq Data

2. TAZRO OHTA @inutano

3. None

4. What do you imagine with a term “Database”?

5. None
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8. Knowledge Scientific data Experimental data

9. Knowledge base Database Raw Data repository

10. Knowledge base Database Raw Data repository

11. What kind of data? Next-generation is already out there…

12. We all need Raw data repo for NGS

13. We’ve already seen WHY WE NEED

14. None

15. Reproducibility is what makes science fair.

16. 2 things required for data repository is…

17. 1: Reliability Data should be archived correctly, with explicit metadata

    2: Accessibility Data should be able to be accessed by anyone, without special trick

18. 1: Reliability needs curation Data should be archived correctly, with

    explicit metadata 2: Accessibility needs good interface Data should be able to be accessed by anyone, without special trick

19. 1: Reliability needs curation Data should be archived correctly, with

    explicit metadata 2: Accessibility needs good interface Data should be able to be accessed by anyone, without special trick

20. 1: Reliability needs curation Data should be archived correctly, with

    explicit metadata 2: Accessibility needs good interface Data should be able to be accessed by anyone, without special trick

21. Current Web-interface for DRA http://trace.ddbj.nig.ac.jp/DRASearch

22. Good: Simple, Fast, and no bugs (!) Challenge: Lack of

    metadata caused “NOT FOUND”

23. PROBLEM:

24. ???

25. DRASearch can NOT find Data without metadata …but they definitely

    exist in the repo.

26. Too many to ask submitters; then we implemented a system

    to make metadata rich enough

27. 2 sources into DRA DDBJ Read Archive

28. Publications can have details of seq process, Seq Read Quality

    can be a source of data quality. DDBJ Read Archive PubMed PMC Extracted Read Quality

29. And then: integration enables to implement Efficient Data Search

30. Available via DBCLS SRA http://sra.dbcls.jp/

31. Available via DBCLS SRA http://sra.dbcls.jp/

32. Available via DBCLS SRA http://sra.dbcls.jp/

33. Power of Integration: Metadata Search http://sra.dbcls.jp/search

34. Power of Integration: Metadata Search http://sra.dbcls.jp/search

35. Power of Integration: Metadata Search http://sra.dbcls.jp/search

36. 83% seq reads satisfied average quality over 30 0.03% of

    seq reads fall into over 50% N content

37. 1: Reliability from paper/data qual more description brings more proof.

    2: Accessibility from text-search Search included publication brings flexibility.

38. 2.20% of submitted projects has at least one publication 4429

    / 201558 PROBLEM:

39. NIH Data sharing Guideline http://www.niaid.nih.gov/LabsAndResources/resources/dmid/Pages/data.aspx

40. NIH Data sharing Guideline http://www.niaid.nih.gov/LabsAndResources/resources/dmid/Pages/data.aspx

41. What is Next-step to carry on?

42. 1: Beyond Raw Data Archive is going to handle alignment

    data. 2: Analysis Reproducibility Public repo for analysis pipeline is required.

43. 1: Beyond Raw Data Archive is going to handle alignment

    data. 2: Analysis Reproducibility Public repo for analysis pipeline is required.

44. Database is for Biologists not for developers.

45. Thank you! t.ohta@dbcls.rois.ac.jp http://speakerdeck.com/inutano