What is the transcriptome and why study it?
Molecular biologists study a broad spectrum of topics relating to the molecular regulation of cell biology, from DNA and RNA, to protein expression and protein-protein interactions. A dominant theme in molecular biology is how variation in nucleic acids (genotype) affects the biology of organisms (phenotype). The second major theme is the study of gene expression and the resulting change in observed features of a studied sample.
Next Generation Sequencing (NGS) is a key technology enabling an unprecedented level of precision and efficacy in understanding genomic and transcriptomic regulation. A Next Generation sequencer creates a digital file representing sequenced DNA or RNA. This file contains information where nucleotides are represented by letters corresponding to their “bases”.
Next Generation Sequencing data analysis is often referred to as “RNA-seq”. The purpose of this analysis is to map the short reads from raw sequence files to the reference genome and then study the abundance of RNA mapped to a particular region. The abundance can represent levels of gene or isoform expression and can be compared between samples or groups of samples.
Course objectives and methodology
The goal of this course is to prepare a student for real-world applications of RNA-seq. We will review methods of quantitative and qualitative analysis of RNA in a sample, how data is generated using Next Generation Sequencing and use a sample project “Patient Derived Xenograft: Transcriptomic Biomarkers of Breast Cancer” to practice generating a table of expression from raw FASTq files. We will also learn to preview and visualize the resulting data using Principal Component Analysis (PCA). To perform the example analysis detailed in the course, students will need access to the T-BioInfo platform. Account information can be requested in an email to email@example.com. Microsoft Excel is also used for plotting results.
We would like to thank the following people who helped to prepare the projects, develop the tools, and compile the the learning resources for this course:
Dr. Leonid Brodsky and the Tauber Bioinformatics Research Center, Dr. Claudia Copeland, Dr. Ron Ferrucci, Julia Panov, Jaclyn Williams
- Lectures 7
- Quizzes 2
- Duration 6 hours
- Skill level All levels
- Language English
- Students 1827
- Certificate Yes
- Assessments Yes
From biological samples to RNA reads
From raw RNA-seq reads to expression table
A wonderful start to Transcriptomics
The course is well written and quite informative,it makes the concept easy to understand.
Excellent!! to start with Transcriptomics
It’s really a very enlightening course on the topic of transcriptomics . It has awesome content on the concepts with excellent examples on the data analysis and nice guiding videos. I really loved to go through this course.
Very Intuitive and Tough made simple.
It was my first experience with Transcriptomics and I would first like to mention, T BioInfo Platform is very intuitive. The labels are very well designed and visually and logically organized. The possible steps that one can take after selecting an option get highlighted which makes it very easy to focus on what you want to do next, or if you are a bit confused then what you can do next. The course is wonderfully designed. It takes you through principles of Transcriptomics in a step-by-step manner. The course content avoids unnecessary jargon rather, it tries to make sure that you know what you are doing or you can interpret and understand the results. All course lectures in text and videos are really good.
Transcriptomics 1 : A perfect start towards understanding RNA-seq
This course is designed in a very scientific and beautifully structured way; from learning basics of transcription in biology, mRNA quantifying to understanding the logical steps of mRNA data reads analysis, different algorithms used to analyze RNA raw data, their workflow and ultimately statistical analysis regarding gene expression with its biological interpretation. This course also gives the chance to create and work with server pipelines and generating output files which is very much crucial for application in practical world for a solution of a real-life problem.
Great course on Metagenomics
This course explains the underlying concepts of transcriptomics and provides a brief exposure of machine learning and its integration with transcriptomics. It has efficiently described the logical steps for analyzing RNA-seq raw data, which is very helpful and knowledge gaining.