Statistical Analysis of RNA-seq Data

With the advancement of next-generation sequencing (NGS) technology, RNA-seq has been the standard method to profile the whole transcriptome. To tackle the huge amount of data generated by the experiments, computational and statistical methods have been developed. In this lecture, we will cover many aspects of RNA-seq experiments, from experimental design to down stream data analysis. We will focus on statistical considerations in data quantification, normalization, differential expression analysis and pathway analysis.

ACCREDITATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences is accredited by the ACCME to provide continuing medical education for physicians.

CERTIFICATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences designates this live activity for a maximum of 3.0 AMA PRA Category 1 Credit(s)TM.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CREDIT: This program is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001412.