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© 2008 LabKey Software Simplifying Scientific Data Management with LabKey Server January 29, 2009 Presenter: Peter Hussey,

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Presentation on theme: "© 2008 LabKey Software Simplifying Scientific Data Management with LabKey Server January 29, 2009 Presenter: Peter Hussey,"— Presentation transcript:

1 © 2008 LabKey Software www.labkey.com Simplifying Scientific Data Management with LabKey Server January 29, 2009 Presenter: Peter Hussey, peter@labkey.com

2 Agenda  The Problem  The LabKey Server Solution  Working with Assay Datasets (demo)  Benefits  Questions and Next Steps If you think of questions during the presentation, use the chat feature of GoToMeeting. You can also ask questions over the phone at the end of the presentation.

3  Instrument data lives in many small files  File per chip/plate/run  On researcher’s PCs  Separated from clinical data The Problem: Scattered Research Data Lab Scientists Clinicians Principal Investigators and Statisticians Research Subjects  Making it difficult to answer questions like  Where are the results from the Luminex tests we did last May?  What is the average immune response 6 weeks after an event?  How do participant X’s physical exams correlate with his gene expression results over time?

4 The LabKey Solution Lab Scientists Clinicians Principal Investigators and Statisticians Research Subjects  A lab data repository and portal  Based on a robust SQL database  Accessible via secure web pages  Easy and powerful LabKey Server

5 LabKey Study Framework  Assay data comes in many shapes  Instrument-specific formats  A LabKey study links assay data to  Specimens  Participants (subjects)  Time  Metadata is vital for consolidation  Who, what, where, when, how an assay was run  Custom categories  Often neglected Participant Specimen Time point Vial (sample) Assay X data Assay Y data Run Cohort Demographics

6 Demonstration Scenario  Research project: identify the measurable changes that occur around the incidence of a specific viral infection.  Subjects: human participants from at-risk populations who agree to monthly clinic visits and blood draws.  There is no fixed schedule of visits. We are interested in the changes that occur on a monthly basis.  Participants start on different dates.

7 Choosing Timepoints in a LabKey Study  My research does not measure changes over time.  Use the date a test was run as your timepoint. Useful for: –finding or grouping results –assessing instrument calibration  Example: Comparative studies on samples from a tissue bank – “How do the results we’re getting now compare to those we were seeing back in March?” OR  My research follows subjects over time. OR  My research has a detailed schedule of visits.

8 Calendar JanFebMarApr Date-based Study, Single Start Date Study Timeline Month 1Month 2Month 3 Affy Array NAb ELISpo t run Luminex Sample S1 Month 4 Sample S2 Affy Array NAb ELISpo t run ELISpo t rerun Study Start Date

9 Choosing Timepoints (2)  My research does not measure changes over time. OR  My research follows subjects over time.  Time intervals are the interesting data  Example: cancer study in mice, with mouse exposed to a carcinogen and then tested weekly –“On average, how long does it take for the tumor to reach a given size?” OR  My research has a detailed schedule of visits.

10 Calendar JanFebMarApr Date-based Study, Separate Start Dates Study Timeline Expose Jan 5 Blood Draw Jan 19 Blood Draw Feb 24 Biopsy April 5 Subject M Subject N Expose Feb 4 Blood Draw Feb 18 Blood Draw Mar 18 Day 1Day 14Day 42Day 90 M’s Start Date N’s Start Date

11 Choosing Timepoints (3)  My research does not measure changes over time. OR  My research follows subjects over time. OR  My research has a detailed schedule of visits.  Visits: planned dates with protocols for clinical tests and specimen draws  Example: study of volunteers at risk of contracting malaria –“What changes do we see in the blood assays in the 6 months after first exposure ?”

12 Calendar JanFebMarApr Visit-based Study Study Timeline Intake Visit Week 2 Visit Week 6 Visit 3 Month Visit Intake Jan 5 Visit Jan 17 Visit Feb 25 Visit Apr 3 Participant A Participant B Intake Feb 4 Visit Feb 18 Visit Mar 18

13 Agenda  Describing the Problem  The LabKey Server Solution  Working with Assay Datasets (demo)  Create a study, define timepoints, load specimens  Define and load demographic and clinical data  Define an assay and customize metadata –General type –Built-in specialized types: ELISpot, NAb, Luminex,…  Load assay datasets  Navigate and analyze the consolidated data  Benefits  Questions and Next Steps

14 Assay Architecture  Assay Design Types  Built for specific data formats (instrument output)  Know how to parse the assay data and where to store it  Specify default metadata and custom design page(s)  Written in Java –Can be installed on the server as an external module –Can derive from existing functionality (e.g. plate layout editor) –Coming in next release: configurable  Named Assay Design  Named customization of metadata for a design type  Metadata fields describe –Data type, valid ranges, pattern checks –Upload form UI: labels, select lists, help text

15 Assay Architecture (2)  Import Data  Upload a group of data files at one time  Specify metadata for entire group and for individual runs  Definition of a run determined by Assay design type  Copy to Study  Separation of upload step from data integration step  Matches data based on choice of keys –Specimen ID –Participant ID and timepoint / visit –ID Mapping file / spreadsheet  Lets users curate data prior to “publishing” in study

16 LabKey Assay Forms  Example barcodes for specimen identifiers shown at right  Barcode reader acts as keyboard in assay upload forms

17 Benefits of Assay Data Management  Improved Data Quality  Limit data entry errors –Select lists, smart defaults –Range and pattern checks  Stage data before making public  Broader Uses of Data  LabKey tools: Navigator, charting, reports  External languages: R, JavaScript, SAS  Standardization  Lexicon  Best practices  Rapid Adaptation  Define new formats and metadata as needs change

18 Agenda  Describing the Problem  The LabKey Server Solution  Working with Assay Datasets  Benefits  Questions and Next Steps

19 Next Steps  Explore LabKey Server at www.labkey.orgwww.labkey.org –Documentation –Videos –Demo data –Support boards –Windows-based evaluation server  Contact LabKey Software (www.labkey.com)www.labkey.com –Email sales@labkey.comsales@labkey.com –Ask us to send our whitepaper on LabKey in HIV/AIDS research (Feb ’09) –Interested in trying LabKey as a hosted web service? We are looking for some beta customers –Give feedback on this and future webinars

20 Thank you! --The Management


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