Welcome to the Workshop!

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This workshop aims to cultivate a group of people at Penn who have the knowledge and skills to develop customized data analysis algorithms for the complex data generated in flow cytometry.  As a scientist who uses flow cytometry in your research, you are well aware of the power of the technology and the complexity of the data it generates, as well as with the difficulties and limitations of conventional data analysis approaches based on manual sequential gating.

In this workshop you will learn to wield a set of tools based upon the R Statistical Programming Environment and Bioconductor.  With these tools, and armed with knowledge of some best programming practices, you will be able to create data analysis approaches that are limited only by your own imagination and creativity.  You will also learn how to collaborate in teams to develop programs, thereby leveraging your software development efforts.

Developing such analysis algorithms is not for the faint of heart.  You will need to spend considerable effort to internalize these new skills and will undoubtedly encounter many frustrations.  However, I hope you will be rewarded with a powerful skill set that will not only help you overcome obstacles in discovering new knowledge from your experimental data, but will also serve you well in your career going forward.

I owe a great debt of thanks to Dan Bieting for permission to borrow from his course on R for transcriptomics, as well as his advice on course mechanics.  I also want to thank Herb Holyst who has been a great partner with me developing this workshop.  Thanks Dan and Herb!