Batch Correction and Sample Randomization
Presenter: Duncan Donohue, PhD, Statistical Consulting and Scientific Programming Group, Computer and Statistical Services, National Cancer Institute at Frederick, Data Management Services, Inc. a BRMI company.
In this talk we will discuss how and why to minimize and correct for batch effects in our experiments. We will cover appropriate sample randomization and several computational methods to help uncover and mitigate batch effects. A working knowledge of R will be useful but is not required.
This will be a hybrid event. To register, please visit the following link: https://cbiit.webex.com/weblink/register/r8b8989ae7ed0b9a2b84ce7c8efe25de1.
This session will be recorded, and materials will be shared with attendees a few days after the event.
For additional details and questions, please contact Natasha Pacheco (email@example.com), Advanced Biomedical Computational Science group, Frederick National Laboratory for Cancer Research.
Tue, Sep 12
12:00 PM - 1:00 PM