Bioinformatics Methods for Transcriptomics
Offered By: Johns Hopkins University via Coursera
Course Description
Overview
This course will cover bioinformatics methods for analyzing transcriptomic RNA sequencing data generated with the short read (RNA-seq) and long read (PacBio, ONT) sequencing. In its four modules, the course addresses the core transcriptomics questions: What are the genes and transcripts expressed in a given sample or condition of an experiment?, What are their expression levels?, and What are the differences in gene expression and splicing patterns between conditions? It provides hands-on instruction on how to use popular and/or emerging tools such as STAR, PsiCLASS, DESeq2, rMATS, MntJULiP, Minimap2 and IsoQuant. This is an intermediate level course, and assumes basic knowledge on using command line bioinformatics tools in a Unix-type environment.
Syllabus
- Module 1: Course Introduction and Gene expression analysis of RNA-seq data
- Module 2: Alternative splicing analysis of RNA-seq data
- Module 3: Transcriptome reconstruction with long RNA sequencing reads
- Module 4: Differential expression and differential splicing analysis with long RNA sequencing reads
Taught by
Liliana Florea, PhD
Tags
Related Courses
Network Analysis in Systems BiologyIcahn School of Medicine at Mount Sinai via Coursera Molecular Dynamics for Computational Discoveries in Science
University of Massachusetts Boston via Independent Biology Meets Programming: Bioinformatics for Beginners
University of California, San Diego via Coursera Python for Informatics: Exploring Information
Open Education by Blackboard Genomic Medicine Gets Personal
Georgetown University via edX