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2018 Workshops

Analysis of Biological Images with CellProfiler
CellProfiler is an open-source, freely-downloadable software designed for large-scale, automated analysis of biological images. Attendees will have a hands-on experience with CellProfiler, followed by case-studies on High Content Screening and cell-type classification. At the end of the workshop there will be a breakout session where attendees receive guidance on analyzing their own image data.
 
May 16
An Introduction to Image Analysis with CellProfiler
CellProfiler is an open-source, freely-downloadable software designed for large-scale, automated analysis of biological images. Attendees will have a hands-on introduction to CellProfiler, followed by case-studies on High Content Screening and cell-type classification. At the end of the workshop there will be a breakout session where attendees will receive guidance on analyzing their own image data. If you are curious about automating the analysis of your microscopy data or want to become familiar with "what's possible", come to the workshop and see what's new in CellProfiler for 2018.
 
March 28
 
Using Morpheus for Matrix Visualization and Analysis
In this hands-on workshop, participants will learn to use Morpheus, a web-based application for matrix visualization and analysis. Participants will learn how to interact with multiple data types (e.g., gene expression and mutation in a heat-map-based view) and how to cluster, sort, and filter their data.
 
March 5
 
Proteomics Toolset for Integrative Data Analysis
The Proteomics Platform develops and applies advanced quantitative proteomics methods to a variety of biological questions. To enable proteomics researchers to interactively explore the acquired data matrices of quantified proteins or post-translational modifications and to facilitate an integrative set of analysis tools, we have developed the Proteomics Toolset for Integrative Data Analysis (Protigy). Primarily developed for the Proteomics Platform, we are proud to open access to our tools to a broader audience. Protigy streamlines proteomics data analysis, provides an intuitive interface for lab researchers to analyze and explore proteomics datasets, and ensuring reproducible data analysis by keeping track of workflows and parameters. Some of the features of Protigy that we may cover in the workshop include:
  • Data normalization/filtering
  • Data QC
  • Marker selection
  • Interactive visualization of results
  • Integration of protein-protein interaction databases
  • Saving analysis sessions and sharing with collaborators
  • Export of results in Excel and PDF formats

The last part of the workshop will be a hands-on session in which participants will analyze proteomics datasets provided by the instructors. Protigy has been implemented as R/Shiny app and runs on a commercially licensed Shiny Server Professional maintained by the Proteomics Platform which will be partly used throughout the workshop. In order to guarantee all participants can take part in the hands-on sessions, participants are encouraged to bring their own laptops. We will demonstrate how to install and use Protigy on Windows/Linux/Mac computers. Protigy can be freely accessed on GitHub (https://github.com/karstenkrug/modT).

 
 
February 28
 
 
Integrative Genomic Analysis with GenePattern
GenePattern enables researchers at all levels of computational expertise to use hundreds of tools for the analysis of gene expression, sequence variation, proteomics, and more, through an intuitive interface that requires no coding.

GenePattern makes reproducible research easy: analyses can be rerun at any time with the same inputs; every version of each tool is tracked, so that a result can be reproduced even if the code that produced it changes in the future; and researchers can chain analyses together to encapsulate and share their research as reproducible workflows.

A new GenePattern Notebook (http://www.genepattern-notebook.org/) environment based on the popular Jupyter Notebook system, further allows users to interleave text, graphics, and analyses in unified "research narratives" that can be shared and published.

 
In this hands-on workshop, participants will learn how to:
  • Analyze and visualize gene expression (including RNA-seq) and other genomic data
  • Identify GenePattern analyses relevant to their scientific objectives   
  • Ensure that their analyses are reproducible
  • Create and publish research narratives that serve as a live, executable, sharable representation of a study
 
 
February 5