May 1, 2024
3 minute read
RNA-Seq is a revolutionary technology that has revolutionized the field of molecular biology. It is a powerful technique used to study the expression of genes, identify genetic variants, and analyze the structure and function of RNA. With its ability to generate vast amounts of data, RNA-Seq has enabled researchers to gain unprecedented insights into the complex world of gene regulation and cellular processes.
What is RNA-Seq?
RNA-Seq, short for RNA sequencing, is a high-throughput sequencing technology that allows scientists to determine the sequence of RNA molecules in a biological sample. RNA molecules, including messenger RNA (mRNA), ribosomal RNA (rRNA), and small non-coding RNAs, play crucial roles in various cellular processes.
In RNA-Seq, RNA molecules are extracted from a sample and converted into complementary DNA (cDNA) through a process called reverse transcription. The cDNA is then sequenced using next-generation sequencing (NGS) platforms, generating millions of short sequence reads.
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Find a path to becoming a RNA-seq. Learn more at:
OpenCourser.com/topic/291vlu/rna
Reading list
We've selected four books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
RNA-seq.
Provides a comprehensive overview of RNA-Seq technology and its applications. It covers the principles of the technology, the different types of RNA-Seq experiments, and the data analysis methods used to analyze RNA-Seq data.
A comprehensive and up-to-date guide to RNA sequencing techniques and analysis, covering the entire process from sample preparation to data interpretation. Written by leading experts in the field.
A practical guide to RNA-Seq data analysis, covering all the essential steps from data import to visualization and interpretation. Written by experienced bioinformaticians.
Provides a practical guide to analyzing NGS data, including RNA-Seq, ChIP-Seq, and exome sequencing. It covers the key steps of data analysis, including read alignment, quality control, and data interpretation.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/291vlu/rna
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