Batch Correction and Sample Randomization

About this Class

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. 

This session will be recorded, and materials will be shared with attendees a few days after the event. For details, please contact Natasha Pacheco (natasha.pacheco@nih.gov), Advanced Biomedical Computational Science group, Frederick National Laboratory for Cancer Research.

You will receive a confirmation email with the Webex login information.