2013 Duke CFAR Flow Cytometry Workshop

1. 2013 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. Example of Completed MIFlowCyt Checklist for Cytometry Publication

4. 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..

5. 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 relavant • Repository within a particular institution • Institutions are interested in archivng data

6. Why is Annotation important?

7. 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

8. 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?

9. 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!!!

10. 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

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

12. 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

13. Keywords within Experiment Layout

14. 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

15. 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

17. Softwares ???? • Cytobank • Open access publications • Data respository within you organization

18. Tube List

19. Random notes • Minimum information • Metadata?? • Cytobank • Flow Repositiory