Das Herbstsemester 2020 findet in einer gemischten Form aus Online- und Präsenzunterricht statt.
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636-0202-00L  Lab Course: Next-Generation Sequencing

SemesterHerbstsemester 2018
DozierendeR. Paro, S. Reddy
Periodizitätjährlich wiederkehrende Veranstaltung
LehrveranstaltungFindet dieses Semester nicht statt.
LehrspracheEnglisch
KommentarOnly for Biotechnology MSc, Programme Regulations 2017.

Attention: this lab course will be offered again in Spring semester 2019.


KurzbeschreibungThe Lab Course will take place Monday/Tuesday 9-17h, 10 days in total, start of this lab course is on Monday, September 25 2017.
LernzielStudents 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.
InhaltIntroduction 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.
SkriptMaterial will be provided during the course
LiteraturSara 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.