Past Workshops

Firehose Workshop
This workshop will have 4 sections.
  1. Introduction: This section will cover history, current stats, and the conceptual framework of Firehose, and will demonstrate the many FH workflows (e.g., GDAC, GTEx) and the many tools available.
  2. How to run a project: This section will focus on the actual process of running a project in Firehose and discuss Firehose features and tools. It will describe the steps needed to set up and run a project in Firehose including importing data, using workflows, working with samples (sets, pairs, and individuals), and running tasks.
  3. Advanced: This section will describe some more advanced features of Firehose along with basic troubleshooting, and will cover the use of FUSE and Redshirt.
  4. Tool installation: This section of the workshop will demonstrate the steps necessary to put a tool into the Firehose workflow. This section is for tool builders and more advanced users of Firehose.
  October 2    
   
Statistical Genetics
This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches.

The workshop will be a blend of lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis. Tutorial datasets will be provided for the introduction to the analysis of genetic data. Participants will not need to bring a laptop, as computers will be provided. At the end of the workshop, participants should have a basic understanding of the elements of genetic analysis for common and rare variation. In particular, this workshop will provide a foundation for starting genetic analysis of real data and an introduction for how best to learn more about current techniques. The practical components of the workshop will include command line work, so basic familiarity with Unix environment is strongly recommended.  
  September 29    
   
   
Using CellProfiler for Biological Image Analysis
This workshop will instruct participants in the use of CellProfiler, an open-source, freely-downloadable software package designed for large-scale, automated phenotypic image analysis. Attendees are encouraged to contribute sample images from their assays as part of the demonstration. We will also briefly discuss the basic principles of supervised machine learning in order to score phenotypes where phenotypic differences between samples are not visible by eye.
  September 19  

 
   
GenePattern
Participants will learn to use GenePattern features, including an intuitive graphical user interface for users at all levels of computational sophistication; a comprehensive repository of clustering, prediction, preprocessing, and visualization modules for analysis of microarray data; a pipeline environment that allows users to chain tasks together to create and share methodologies; a module integration environment that allows rapid, code-free integration of new tools; and a programming environment that allows users to access GenePattern modules from the Java, MATLAB, and R programming languages.
  September 12   Workshop Materials
   
Strategies for Visualizing Data
Data visualization is becoming increasingly important in biomedical research as a means to explore data for patterns and relationships. Such exploration, driven by the graphical representation of information, is the critical first step to inform subsequent computational and machine-driven approaches to data analysis. The process requires us to further define clear objectives and improved implementation to be successful. Data for the most part have no natural form or “look” - we have to make choices about how they are displayed. Each decision can bring out certain kinds of patterns in data while hiding others. We rely heavily on our intuition, common sense, and precedent in published material when we visually depict data. This is largely an unscientific process. In this workshop we will explore systematic approaches that rely on core graphic design principles and vision science (i.e. how we decode information encoded in graphical form) to develop effective visualizations of data.
  July 21   Workshop Materials
   
Introduction to the Integrative Genomics Viewer (IGV)
In this course, participants will learn to use the Integrative Genomics Viewer (IGV) to view different types of genomic data. Topics covered include:
  • Overview of the IGV user interface
  • Viewing copy number data
  • Viewing DNA sequencing alignments, including single nucleotide variants and structural events
  • Viewing RNA-Seq data
  • Viewing ChIP-Seq data
  • Using IGV tools

The course will include both lecture and hands-on exercises.

  June 27   Workshop Materials
   
Using CellProfiler for Biological Image Analysis
This workshop will instruct participants in the use of CellProfiler, an open-source, freely-downloadable software package designed for large-scale, automated phenotypic image analysis. Attendees are encouraged to contribute sample images from their assays as part of the demonstration. We will also briefly discuss the basic principles of supervised machine learning in order to score phenotypes where phenotypic differences between samples are not visible by eye.
  June 6    
   
Single-Cell Genomics: Theory & Practice
Emerging genomic technologies now allow for deep and unbiased profiling of single cells and represent powerful approaches for characterizing and dissecting cellular behaviors in complex and heterogeneous tissues. This workshop is intended to provide a practical and hands-on introduction to the experimental and computational aspects of single-cell analysis, with an emphasis on single cell RNA-Seq. The workshop will be divided into two portions: first, we will describe and demonstrate experimental approaches to single cell genomics; then, we will introduce computational approaches for QC and analysis of single cell data, focusing on recently published single-cell RNA-Seq datasets.
  June 2  

 
   
Genome Engineering Using CRISPR-Cas9
Recent advances in genome-engineering technologies based on the CRISPR-associated RNA-guided endonuclease Cas9 are enabling the systematic reverse engineering of mammalian genome function. Derived from prokaryotic immune systems, Cas9 can be targeted to specific locations within the complex, mammalian genome using short RNA guides. DNA sequences within the endogenous genome and their functional outputs are now easily edited or modulated in virtually any organism of choice, empowering researchers to elucidate the functional organization of the genome at the systems level as well as establish causal linkages between genetic variations and biological phenotypes. In this workshop, we describe the applications of Cas9 for a variety of research or translational applications and highlight challenges and important experimental considerations. The development of these remarkable microbial defense systems is driving innovative applications from basic biology, to biotechnology and medicine.
 
  May 13    
   
Charting the Epigenome with ChIP - Basic Analyses of ChIP-Seq Data
ChIP (chromatin immunoprecipitation) is a very powerful technique that enables the localization of proteins on DNA throughout the genome. The technique relies on the selective enrichment of a chromatin fraction containing a specific antigen, by immunoprecipitation. Antibodies that recognize a protein or protein modification are used to capture the chromatin (protein - DNA complex), and in the contemporary method of ChIP-Seq, Nextgen sequencing libraries are derived from the recovered DNA. The libraries are sequenced and the recovered sequences are aligned to a genomic scaffold to map the locations of the antigen recognized by the antibody. The ChIP technique can be used in any area of research to further elucidate gene function and regulation in their native state.

Application of ChIP to the genome wide localization of DNA binding proteins, transcription factors, chromatin modifying enzymes, and histone modifications has helped develop an understanding of the mechanisms for the regulation of chromatin organization. These methods have contributed to our understanding of embryogenesis and tissue specific cellular differentiation, while aberrant chromatin structure is associated with development disorders and other diseases, such as cancer.

The workshop will cover the following topics:
  1. Introduction to chromatin, ChIP and usages of the method.
  2. Overview of genomic approaches to map in-vivo chromatin structure (ChIP-Seq).
  3. Detailed description of genome-wide mapping of chromatin by ChIP-Seq - e.g., analysis methods, validations, sample requirements, reproductibility, quality assessment and materials validation.
  4. Use of visualization tools such as IGV and UCSC Genome Browser.
  5. Major scientific discoveries stemming from charting of in-vivo chromatin maps - chromatin states, enhancer mapping, organization of the chromatin regulators, dynamics of transcription factors binding.
  May 9   Workshop Materials and Videos
   
Statistical Genetics
This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches.

The workshop will be a blend of lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis. Tutorial datasets will be provided for the introduction to the analysis of genetic data. Participants will not need to bring a laptop, as computers will be provided. At the end of the workshop, participants should have a basic understanding of the elements of genetic analysis for common and rare variation. In particular, this workshop will provide a foundation for starting genetic analysis of real data and an introduction for how best to learn more about current techniques. The practical components of the workshop will include command line work, so basic familiarity with Unix environment is strongly recommended.  
  April 14  
 
   
Genetic Perturbations for Functional Genomics: RNAi, CRISPRs, ORFs
The Genetic Perturbation Platform (formerly known as RNAi) workshop will explore functional genomics resources as the Broad, both for those interested in performing genetic screens and for those interested in using these tools to answer specific questions in their area of interest. The workshop is aimed at bench scientists who might use these resources as well as computationalists who want to understand more about biological mechanisms and experimental approaches underlying the data sets that emerge. We will cover the range of perturbations available in the Platform, including shRNAs, ORFs, and CRISPRs, including background on how they work and how they are delivered into cells. We will then discuss the planning and execution of small scale and genome-wide screens using these reagents. Additionally, we will provide hands-on examples of how to analyze and prioritize hits that emerge from screens, and discuss how to move from primary screening data to figures 3 through 7 of your publication. 
  January 13