Location: MTZ Seminar Room, Pauwelstr, 19; 3rd Floor, Corridor B room 3.04.
Dates: Monday 9:30-12:30 (starting 29.04.2019)
Prerequisite (desirable): Introduction to Bioinformatics
Credits: 7 (10 with extra work for Media M.Sc. Students)
Lecturers: Ivan G. Costa
Evaluation: 20% prototypes / 60% final project / 20% presentation
RWTH online description: Bioinformatik Praktikum
Description:Next-generation sequencing (NGS) allows the measurement of molecular characteristics of individuals on a genome-wide scale. The application of NGS methods to large patient groups enables precise medicine, i.e. finding genetic features to guide medical treatment. The low level analysis of NGS data imposes large computational and statistical challenges. NGS data are typically large (1 to 100 GB per sample/patient) requiring efficient computational strategies for data analysis and storage. Moreover, NGS data contains artifacts and noise, which affects the reliability of predictions and leads to errors.In this software lab, we will explore computational problems associated to the analysis of single cell sequencing data. Students will implement strategies based on machine learning and statistical methods to analyze single cell sequencing data. We will use the high-performance cluster and GPUs from the ITC RWTH Aachen as the computational platform for this course.
29.04.2019 –Introduction to Bioinformatics and Next Generation Sequencing [Lecture 1]
13.05.2019 – Introduction to HPC clusters and GPUs [Lecture 3]
20.05.2019 – Project Description [Lecture 4]
27.05.2019 to 8.07.2019 – Project Development
15.07.2019 – Project Presentation
Literature & Videos
Pavel A. Pevzner and Phillip Compeau, Bioinformatics Algorithms: An Active Learning Approach.
Check for Chapter 9 for some algorithms on short read alignment
Advanced Single Cell Analysis – Hemberg Lab