RNA Seq Analysis

Xiangqin Cui, Ph.D.

Xiangqin Cui, PhD
Atlanta VA Medical Center
Emory University

Dr. Cui received her Ph.D in Genetics at Iowa State University in 2001. She was then trained in in statistical genetics as a postdoc at the Jackson Laboratory. Dr. Cui joined Section on Statistical Genetics, a division of the Department of Biostatistics in School of Public Health at the University of Alabama at Birmingham in Aug 2004 as an Assistant Professor with a joint appointment in the Biostatistics Department and the Department of Medicine (Division of Genetic and Translational Medicine). Her research interest at UAB includes statistical genomics, epigenomics, proteinomics, metabolomics, microbiomic, immune-Repertoire, and other high throughput study design and data analyses. Dr. Cui moved to Emory University in September 2017 and took on the job of building a data analytics core in the Atlanta VA medical center. Scientifically, Dr. Cui has been heavily involved in studies of cancer, kidney diseases, cardiovascular diseases, and autoimmune diseases.

Course Contents

Quantitative transcriptome analysis using RNA-seq is a two-step process. The heavy upstream bioinformatics process deals with handling of raw sequencing reads data, quality controlling the reads and aligning them to a certain version of reference genome. The downstream statistical steps involve read count quantification, normalization of reads and estimation of gene expression differences and identification of differentially expressed (DE) genes between biological groups of samples. In this analytic hands-on session, we will be performing differential gene expression analysis on already quantified raw read counts data. Popular DE analysis programs like EdgeR, DESeq and limma will be showcased for different design conditions of the data.

Transcriptome Analysis Using NGS – 7th Short Course on NGS
Published on December, 2017

Transcriptome Analysis using RNA-Seq Data
Published on March, 2018