Scientific Tutorials are open to all Full Congress
Registrants; no additional fees apply.
Saturday, June 10, 2017
9:30 – 11:00
Introduction to CellProfiler, Free Open-Source Software for Image Analysis
Kyle Karhohs, Broad Institute
Beth Cimini, Borad Institute
Course overview: Microscopy experiments have proven to be a powerful means of generating information-rich data for biological applications. From small-scale microscopy experiments to time-lapse movies and high-throughput screens, automatic image analysis is more objective and quantitative and less tedious than visual inspection. This course will introduce users to the free open-source image analysis program CellProfiler and its companion data exploration program CellProfiler Analyst. We will show how CellProfiler can be used to analyse a variety of types of imaging experiments. We will also briefly discuss the basic principles of supervised machine learning with CellProfiler Analyst in order to score complex and subtle phenotypes.
• Basics of image analysis
• Methods of distinguishing objects of interest from the image background
• Methods of separating clusters of touching objects
• Obtaining measurements from the cell
• Exporting measurements and images
MESF for Flow Cytometry's Limit of Detection: How Low Can You Go?
John Nolan, The Scintillon Institute
Mike D. Leipold, Stanford University, Human Immune Monitoring Center
1. Basic CyTOF background
b. Pros and Cons
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
a. Sample prep - fixation, filtration, etc
b. Calibration drift - salt, detector voltage, mass calibration, etc
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.
- Overview of R and Bioconductor
- Installing R
- Installing libraries in R
- Installing Bioconductor libraries in R
- Introduction to cytometry packages available in Bioconductor
- Introduction to cytometry packages not available in Bioconductor
- Basics of fcs file manipulation in R
- The power of Bioconductor vignettes
- Using a vignette to analyze your own data
- Stringing vignettes together to create your own analysis pipelines
- Further resources to explore
- CyTOF Forum
- Bioconductor mailing list
- Github, sourceforge, reddit discussion boards
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.
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
Single Cell Sorting and Genomics or “One is the loneliest number: the journey of a single cell through cytometry to genomics to bioinformatics”
Pat Rogers, Broad Institute
Objectives: To learn the best practices for sorting single cells on different cell sorters for the range of genomics applications How to set up your facility to facilitate single cell sorting experiments To understand how post sorting handling and storage can affect cells in downstream analyses To recognize warning signs of degraded cells in library construction To get a view of the most commonly used techniques in single cell analyses, including RNAseq, DropSeq, and 10x To learn how to troubleshoot when processes fail
Introduction to Orbit Image Analysis, Open-Source Software for Image Analysis of Whole-Slide Scans
Manuel Stritt, Actelion Ltd.
The Value Proposition
This tutorial is aimed at scientists in academia who are considering starting a company to commercialize their inventions, but who have limited experience in doing so. The goal of the tutorial is to describe (i) what a value proposition is, and (ii) how a startup can define, defend and demonstrate its value proposition. The format will be interactive; incorporating real-world examples, as well as discussion among attendees.
13:30 - 15:00
Biosafety in Flow Cytometry
Kevin L Holmes, NIAID, NIH
Stephen Perfetto, NIAID, NIH
Optimize Your Flow Cytometry - Best Practices for Sample Preparation and Staining
- This tutorial will provide a summary of biosafety principles as they apply to flow cytometry and cell sorting, with emphasis on the 2014 ISAC Cell Sorter Biosafety Standards.
- This tutorial will also provide a forum in which to discuss with experts in the field, specific scenarios that operators or core facility managers encounter.
- After participation in this tutorial the attendee should have a clearer understanding of the principles and practices of biosafety as it pertains to flow cytometry, in particular cell sorting. Additionally, the attendee will have a list of resources to aid in risk assessment and the development of Standard Operating procedures in their own lab.
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
Bruce Bagwell, Verity Software House
In this tutorial, a step-by-step explanation of how t-SNE works will be presented. The tutorial will present some of the problems with the original implementation which dramatically limited its potential resolution of cytometry-defined cellular populations. A new variant of the method called Verity Cen-se’ will be presented that is considerably faster than the original method and presents populations in unprecedented high-resolution. Several examples and experiments demonstrating the value of this tool will also be presented.
Advanced, Open-Source Data Analysis Workflow for Imaging Flow Cytometry
Holger Hennig, Broad Institute
Minh Doan, Broad Institute
Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differences among complex, often heterogeneous biological samples.
In this tutorial, we demonstrate a pipeline using open-source software that leverages the rich information in digital imagery using machine learning algorithms . Compensated image files (.cif) from an imaging flow cytometer are generated with the software IDEAS from Millipore. The .cif files are imported into the open-source software CellProfiler, where an image processing pipeline identifies cells and subcellular compartments allowing hundreds of morphological features to be measured. This high-dimensional data can then be analyzed with cutting-edge machine learning and clustering approaches using ‘‘user-friendly” platforms such as CellProfiler Analyst. Researchers can train an automated cell classifier to recognize different cell types, cell cycle phases, drug treatment/control conditions, etc., using supervised machine learning. This workflow should enable the scientific community to leverage the full analytical power of IFC-derived data sets.
1.Generating image tiles from .cif files and importing the images tiles into CellProfiler
2.CellProfiler pipeline for object segmentation and extraction of hundreds of morphological features per cell
3.Machine learning using CellProfiler Analyst
4.Machine learning using custom scripts (R, python)
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