636-0202-00L Lab Course: Next-Generation Sequencing
|Dozierende||R. Paro, S. Reddy|
|Periodizität||jährlich wiederkehrende Veranstaltung|
|Lehrveranstaltung||Findet dieses Semester nicht statt.|
|Kommentar||Only for Biotechnology MSc, Programme Regulations 2017.|
Attention: this lab course will be offered again in Spring semester 2019.
|Kurzbeschreibung||The Lab Course will take place Monday/Tuesday 9-17h, 10 days in total, start of this lab course is on Monday, September 25 2017.|
|Lernziel||Students shall obtain a basic understanding in NGS and its application in transcription profiling including theoretical considerations when starting an RNA-seq experiment and the practical hands-on work of library preparation and usage of bioinformatics tools for data analysis.|
|Inhalt||Introduction to NGS technologies and applications. Design of an RNA-seq transcription profiling experiment. Specific treatment of cells (+/- signal-induction) and RNA extraction. Handling and quality control of RNA samples. Sequencing library preparation starting with total RNA. Quality control and quantification of the libraries. Setup of an NGS run and sequencing of the prepared RNA-seq libraries using the NextSeq 500 system. Analysis of the generated sequence data: sequence data QC, criteria for run performance and quality of data; pre-processing of the raw data; mapping sequence reads to a reference sequence; quantification of transcript abundance and differential gene expression.|
|Skript||Material will be provided during the course|
|Literatur||Sara Goodwin, John D. McPherson & W. Richard McCombie. Coming of age: ten years of next-generation sequencing technologies. Nature Reviews Genetics 17, 333-351 (2016)|
Zhong Wang, Mark Gerstein & Michael Snyder. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics 10, 57-63 (January 2009)
Fatih Ozsolak & Patrice M. Milos. RNA sequencing: advances, challenges and opportunities. Nature Reviews Genetics 12, 87-98 (February 2011)
Ana Conesa, Pedro Madrigal, Sonia Tarazona et al. A survey of best practices for RNA-seq data analysis. Genome Biology 2016 17:13.