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2014 Duke CFAR Flow Cytometry Workshop

2014 Duke CFAR Flow Cytometry Workshop. Data Standards and Annotation. What standards currently exist?. International Society for the Advancement of Cytometry (ISAC) Data Standards Task Force (DSTF ): Data file standards Flow Cytometry Standard (FCS) – version FCS 3.1 Gating ML

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2014 Duke CFAR Flow Cytometry Workshop

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  1. 2014 Duke CFAR Flow Cytometry Workshop Data Standards and Annotation

  2. What standards currently exist? • International Society for the Advancement of Cytometry (ISAC) Data Standards Task Force (DSTF): • Data file standards • Flow Cytometry Standard (FCS) – version FCS 3.1 • Gating ML • Calibration and Measurement Standards • Instrument calibration • Fluorescence intensity calibrations • Molecules of Equivalent Soluble Fluorescence (MESF) • Antibody Binding Capacity (ABC) • Equivalent Reference Fluorophore (ERF) • Counting Standards • Immunophenotyping • Clinical cytometry standards • MIFlowCyt: the minimum information about a Flow Cytometry Experiment • Requirement for Cytometry publication • Training and Education • International Cytometry Certification Examination • Flow Cytometry: • International Cytometry Certification Examination • Optimized ImmunoPhenotyping Panel (OMIP) • Bioinformatics Standards for Flow Cytometry – working group • Cellular Assays: • Biosafety • Biosafety in Microbiological Laboratories • OSHA Bloodborne pathogens • Risk Group and Biosafety Level Definitions • Pathogen Safety Database • Biological Risk Assessment Generic Form (CDCs) • World Health Organization Laboratory Safety Manual • ISAC Biosafety Standard for Sorting Unfixed Cells • “Miata” Minimal Information about T Cell Assays

  3. MIFlowCyt

  4. Example of Completed MIFlowCyt Checklist for Cytometry Publication

  5. MIATA- Minimal Information

  6. MIATA-Minimal Information about T-cell Assay

  7. Data Standards

  8. What is Annotation? • Webster’s dictionary: • Annotation: • a note added by way of comment or explanation • Wikipedia: • An annotation is a note that is made while reading any form of text. • These notes.. establishes a summary for and expresses the relevance of each source..

  9. Why is it significant? • A statistian can quickly batch analyze a large amount of information • Data management: Metadata • Data about data. Metadata describes how and when and by whom a particular set of data was collected, and how the data is formatted. Metadata is essential for understanding information stored in data warehouses and has become increasingly important in XML-based Web applications. • Tracking • Easily track which experiments/data are relevant • Repository within a particular institution • Institutions are interested in archiving data

  10. Why is Annotation important?

  11. Goal of Data Annotation • John Altman: “…to include enough information within the FCS file to allow someone else to make sense of the data without requiring cross-references to your notebook.” - Another operator - Researcher - Investigator - Study Monitor - Auditor

  12. Example of how not to annotate data No annotation of experiment: What’s in the experiment? No Annotation of data files: Which file is which? Where are the controls?

  13. Data Annotation - for all 143,280 data points! Study ID Method Assay Name Batch # Operator Sample ID Visit ID Accession # % Viable (Flow) % Viable (Guava) Recovery CD4 count CD8 count Gate Name (Parameter Names) Tube Name File Name • Checking: • X1 - for electronic data • X3 - for manual entry • Requires STRONG statistical support: • Quickly exceeds limits of excel • Format data for statistical analysis • FJ: column (gates) vs row (file) • CSV: column (identifiers) vs row (single value) • Check data • Manual check: 8sec/value x 143280 = 49 days!!!

  14. Data Annotation:Define in Requisition & Protocol(Billing tracked by Investigator/Study & Date) Research Clinical Folder Investigator Study Experiment Investigator & Researcher Init Study & Date [Batch] & Date JS_GA 29Sept08ATTACK 29Sept08 Specimen Investigator & Researcher Init Donor ID & Visit JS_GAAttack 9 Pre Tube Sample ID Stim & Stain 1_Ms 21 FSCMV FS Parameters mAb & Fluor mAb & Fluor Green E CD4 PE Green E CD4 PE [per detector/sample][per detector/sample] JS_GA 1_Ms 21 FS Attack 9 Pre CMV FS File Name Abbreviations: FS, SS, FMO, Iso, RR, RP

  15. Characters & Dates • Characters • Avoid : / > & % # . + - • Examples: CD4 FITC 1:50; Tube#1; CD14+CD19 • Use • Space • _ • Clarify dates • ddmonyyyy (12Nov2009) • ddmonyy (121109) • monddyy (111209)

  16. Tube List

  17. Keywords • a word that serves as a key, as to the meaning of another word, a sentence, passage, or the like: Search the database for the keyword “Ireland.” • Keywords can be entered into the data of a data file for easy searching within a database

  18. Keywords within Experiment Layout

  19. Green Laser (532nm; 150mW) Duke LSRII Red Laser (642nm; 25mW solid state) Duke LSRII Blue Laser (488nm; 20mW) Violet Laser (405nm; 25mW) Duke LSRII Duke LSR II CFSE Alexa 680 515/20 QDot 655 505LP QDot 585 488LP 710/50 685LP 660/40 710/50 PE Cy5.5 SSC Blue 685LP 630LP 585/42 PerCP-Cy5.5 PE TR Am Cyan 710/50 570LP QDot 545 690LP 610/20 515/20 505LP 600LP 560/40 535LP 557LP 575/25 640LP PE- Green 740LP 560/40 660/40 780/40 740LP 450/50 595LP QDot 565 670LP 660/20 PE Cy5 PE Cy7 Cas Blue 780/60 605/40 705/70 APC QDot 605 APC Cy7 QDot 705 Duke University Medical Center Alexa700 FITC CD57 FITC TNF Alexa700 CD8 APC-Cy7 CD4 PerCP-Cy5.5 CD27 APC APC-HL750 CD45RO ECD CD3 AmCyan vAmine PacBlue IL-2 PE vAmine + CD14 PacBlue + CD19 PacBlue INF PE-Cy7 CD107 PE-Cy5 17Apr08, jhe

  20. Instrument configurations • Lasers and parameters of your instrument • May be unique to your instrument • Name style: which give more information? • Fluorochorme and marker • CD4 FITC, CD8 APC Cy-7 • Laser/filter/ fluorochrome/marker • 488nm 530/30 CD4 FITC • 647nm 660/20 CD8 APC Cy-7

  21. Softwares

  22. FlowRepository.org

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