Aug 16-20, 2021

Monday - Friday


1 Hour Lunch Break


Workshop Fee

This five day live remote workshop is ideal for bench and research scientists who are looking for a solid foundation in RNA-Seq, from application, experimental design and sample preparation to post sequencing data processing analysis using latest bioinformatics approaches.

remote learning
Real-Time Interactive Lecture, Laboratory Protocol and Discussion
Team taught by active researchers
Reference Materials Included
Lectures, Lab Protocols, Reference Materials included
Space limited to 24 participants
Save Money and Time
No Travel, Convenient and Cost Effective

Course Co-Director

Allissa Dillman, PhD
Biomedical Data Science Outreach Coordinator

Course Co-Director

Frank Instructor Photo

Frank Castora, PhD
Eastern Virginia Medical School

This workshop is a unique mix of wet bench presentations and electronic laboratory experiences together with a series of lectures spanning introduction to the concepts of RNA sequencing and the analysis of the data generated to the applications of these approaches to understand important biological and/or biomedical processes and problems. At the end of the program, attendees will have had hands-on experience with the more challenging aspects of manual preparation of an optimized RNA library, analysis of RNA sequences from control and Alzheimer’s Disease brain samples, and knowledge of the application of the most current programs to the analysis of these data.

  • Introduction to NGS and Course Overview
  • From Next Generation Sequencing to RNA Seq
  • Introduction to Downstream Analysis
  • Important Considerations for Downstream Analysis
  • Practical Aspects of RNA-Seq
  • RNA Library Preparation Overview; MiSeq Run Monitoring and Quality Control
  • RNA-Seq Gene Expression Data Analysis Pipeline: Methods, Tools and Issues
  • MiSeq Data Analysis – From Analysis to Networks
  • 16S Metagenomics Analysis; Bioconductor and RNA-Seq Data Analysis
  • RNA-seq of the small RNAs
  • RNA-seq data analysis in the context of biological networks
  • The Interplay between Environmental exposures and metabolic disorders – integrating transcriptional changes and pathway analysis
  • Effect of salt loading on RNA-seq analysis of rat supraoptic nucleus transcriptome
  • Basics of statistical analysis of RNA-seq data
  • Sample Preparation and Run Set-up
  • Demo/Hands-on Library Prep Magnetic Beads Separation
  • Illumina MiSeqSequencing of samples from AD brains plus opportunity to sequence RNA from one selected attendee
  • Run assessment
  • PC Based: Using BaseSpace to Analyze RNA-Seq Data
  • Post-RNA Seq Analysis
  • Pathway Analysis
  • Bioconductor and RNA-Seq Data Analysis
  • RNA-Seq Data Analysis in the Context of Biological Networks

Dr. Frank Castora is a Professor of Biochemistry in the Department of Physiological Sciences at the Eastern Virginia Medical School. Dr. Castora has been involved with teaching in or directing a variety of Bio-Trac training programs at the National Institutes of Health as well as other institutions nationally for over thirty years, including workshops in mitochondrial biogenesis and pathology, recombinant DNA technology, PCR, microarray analysis, and RNA-seq. Currently his research interests include mitochondrial DNA mutations and gene expression in AD as well as mitochondrial function in human reproduction and fertility

Guest Speakers and Laboratory Instructors

Kory Johnson, Ph.D.
Dr. Kory Johnson is a bioinformatics working professional with >20 years work experience in biotech and government. Currently, Dr. Johnson works at the National Institute of Neurological Disorders and Stroke (NINDS) at the National Institutes of Health (NIH) as a Staff Scientist in the Bioinformatics Section, serving the Institute as the intramural resident bioinformatics subject matter expert and mentor; performing omics-based research, training, and support since 2006.
James Li, Ph.D.
Dr. James Li is an assistant professor in the department of Biostatics, Bioinformatics, and Biomathematics at Georgetown University. Research focuses on predictive data science, novel computing methods and a variety of their applications, such as natural language processing (NLP) & text mining, ultra-high dimensional "Omics" data analytics, data mining on wearable devices for health, privacy-preserving data mining in healthcare informatics, and big data infrastructure on bioinformatics. Besides his independent research and teaching, Dr. Li also collaborates with biomedical investigators, specifically, applying bioinformatic machine learning to analyze NGS and other high-throughput biomedical research data.
Somiranjan Ghosh, Ph.D.
Dr. Somiranjan Ghosh is an exposure biologist in the capacity of Sr. Research associate at the Department of Biology, and an Adjunct Assistant Professor at the Department of Pediatrics and Child Health in the College of Medicine, Howard University in Washington DC, with 20+ years of research and teaching experience in academia. Current research focus is on the development of early disease biomarkers through molecular transcriptomics and by integrating the prospective pathways, to create a foundation that will advance the identification and understanding of the role of environment on human health and disease (Gene Environment Interactions, GxE).
Dr. Brian SchmidtBrian J. Schmidt, Ph.D.
For the past nine years, Dr. Schmidt has served the Technology Integration Manager and Production Team Leader for a high volume intramural sequencing center, providing contract DNA Sequencing Services, utilizing Illumina, 454, SOLiD and Ion Torrent platforms. Dr. Schmidt brings over twenty five years of Molecular Biology R&D staff scientist experience with Life Technologies, Inc., GeneChoice, Inc. and Genex Corp.
Dr. Niraj TrivediNiraj Trivedi, Ph.D.
Dr. Trivedi is a branch statistician for Columbus Technologies as a contractor for the Social Behavioral Research Branch at the National Human Genome Research Institute (NHGRI) at the National Institutes of Health. Dr. Trivedi provides statistical, computational, and bioinformatic support to scientists of the institute for their data analysis needs. This includes microarray analysis, statistical analysis, and general analysis in biomedical "big data"

The Bioscience Education Center

Montgomery College
20200 Observation Drive
Germantown, MD 20876