2017 Program Scientific Tutorials
Scientific Tutorials are open to all Full Congress
Registrants; no additional fees apply.

Saturday, June 10, 2017

9:30 – 11:00

Advanced , Open-Source Data Analysis Workflow for Imaging Flow Cytometry​

Holger Hennig, Broad Institute
Minh Doan, Broad Instiutute

MESF for Flow Cytometry's Limit of Detection: How Low Can You Go?

John Nolan, The Scintillon Institute

Basic CyTOF

Mike D. Leipold, Stanford University, Human Immune Monitoring Center

1.  Basic CyTOF background
a.  Instrument
b.  Pros and Cons
2.  Spillovers
a.  Oxide
b.  Isotopic
c.  Elemental - impurities, contamination
d.  Abundance sensitivity/mass calibration
3.  Panel Design
a.  Ion transmission efficiency
b.  Sensitivity across mass window
c.  Setting gates
d.  Robustness to biological variation
4.  Operational
a.  Sample prep - fixation, filtration, etc
b.  Calibration drift - salt, detector voltage, mass calibration, etc
c.  Normalization
d.  Reproducibility

Considerations for quality cell sorting

Rob Salomon, Garvan-Weizmann Centre for Cellular Genomics Garvan Institute of Medical Research, Sydney, Australia 
Suat Dervish, Westmead Institute for Medical Research, Sydney, Australia

Cell sorting is more than simply setting drop delays, watching dots on a screen and facebooking your daily news feed. This tutorial will delve into the fundamental questions and processes, both technical and biological, that need to be considered in achieving quality cell sorting.

By providing an overview of various cell sorting technologies along with the strategies to leverage different cell sorting technologies, attendees should gain a clearer understanding of the practicalities of cell sorting in the real world and be able to develop strategies of how best to achieve quality cell sorting outcomes.

Introduction to R

Brian Capaldo, Office of Research Core Adminstration, University of Virginia, Charlottesville, VA 

This course seeks to provide an introduction to R programming and the cytometry focused tools in the Bioconductor libraries.
  1. Overview of R and Bioconductor
    1. Installing R
    2. Installing libraries in R
    3. Installing Bioconductor libraries in R
    4. Introduction to cytometry packages available in Bioconductor
    5. Introduction to cytometry packages not available in Bioconductor
  2. Basics of fcs file manipulation in R
  3. The power of Bioconductor vignettes
    1. Using a vignette to analyze your own data
    2. Stringing vignettes together to create your own analysis pipelines
  4. Further resources to explore
    1. CyTOF Forum
    2. Bioconductor mailing list
    3. Github, sourceforge, reddit discussion boards
  5. Conclusions/Discussion

11:15 - 12:45

“You Can Lead a Horse to Water…” Flow Cytometry Myths Which Still Exist

Evan Jellison, Department of Immunology, UConn Health 
Ryan Duggan, Oncology Discovery, AbbVie, Inc.

Do you have a stubborn student, post-doc, or principal investigator? Have you ever heard, “I’ve always done it this way and it just looks better” or “that’s how our lab has always done it”? From appropriately setting detector voltages to using the proper controls for compensation and gating, flow cytometry can be a complicated enterprise. It’s all too easy to fall back on what works for you or what makes your P.I. happy.
This tutorial will discuss common myths which still exist in flow cytometry and arm attendees with the tools to dispel these myths using actual examples. While the origins of these myths may never be known, their conclusion starts with you.
Optimize Your Flow Cytometry - Best Practices for Sample Preparation and Staining

Ruud Hulspas, Cellular Technologies Bioconsulting, LLC

Non-specific binding of antibodies can obscure data interpretation and even hide cell populations of interest. Aside from the quality of antibodies, sample preparation methods greatly affect the way antibodies bind to their intended, as well as unintended targets.

This Tutorial considers various kinds of ‘background’ in flow cytometry and explains how each kind can be controlled/minimized. Topics include:
  • Antibody performance assessment
  • Antibody titration
  • Isotype controls
  • Internal controls
  • Spectral overlap
  • Clarify that not all background is equal
  • Clarify how controls should be used
  • Raise awareness about relevant literature
  • Share experiences and different points of view
Single Cell Genomics (w/Sorting)

Pat Rogers, Broad Institute

 Introduction to Orbit Image Analysis, Open-Source Software for Image Analysis of Whole-Slide Scans​

Manuel Stritt, Actelion Ltd. 

The Value Proposition

Gillian Isabelle

13:30 - 15:00

Establishing a New SRL Facility -- From Lab Design, Instrument Purchase, Understanding Your User Base​

Michael Thomson, MHTP Flowcore Node, St. Vincent's Institute of Medical Research

Computational tSNE​

Bruce Bagwell, Verity Software House

Introduction to CellProfiler, Free Open-Source Software for Image Analysis​

Kyle Karhohs, Broad Institute
Beth Cimini, Borad Institute

Implementing Best Practices in a Flow Cytometry Shared Resource (Core) Facility

Joanne Lannigan, M.S., School of Medicine Core Facilities, University of Virginia
Monica Delay, M.S., Division of Rheumatology Research Research Flow Cytometry Core, Cincinnati Children's Hospital Medical Center

In November 2016 an ISAC Shared Resource Laboratory (SRL) Task Force published a document outlining a set of “best practices” for SRLs or Core Facilities to use as a general guide for achieving and maintaining standards of excellence in the services they provide. These best practices highlight several important areas that impact the efficiency, quality and reproducibility of services provided by these facilities. The purpose of this tutorial is to provide guidance and generate discussion and feedback on how to best implement these “best practices” across a wide variety and flavors of these SRLs or Cores.


1.    Introduction of the Best Practices and what is hoped to be achieved through implementation
2.    Brief presentation and background information on each topic including SOPs, Training and Education, Quality Assurance, Laboratory Safety, Data Management, Staffing, and Operations
3.    Identification of potential roadblocks and hurdles and how to overcome them
4.    Benefits of implementation and adherence to these best practices