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genome_seq_mobile

Genome Sequencing on Mobile Devices

Assignments

Course Description

Genome analysis is the foundation of many scientific and medical discoveries, and serves as a key enabler of personalized medicine. This analysis is currently limited by the inability of existing technologies to read an organism’s complete genome. Instead, a dedicated machine (called sequencer) extracts a large number of shorter random fragments of an organism’s DNA sequence, known as reads. Small, handheld sequencers such as ONT MinION and Flongle make it possible to sequence bacterial and viral genomes in the field, thus facilitating disease outbreak analyses such as COVID-19, Ebola, and Zika. However, large, capable computers are still needed to perform genome assembly, which tries to reassemble read fragments back into an entire genome sequence. This limits the benefits of mobile sequencing and may pose problems in rapid diagnosis of infectious diseases, tracking outbreaks, and near-patient testing. The problem is exacerbated in developing countries and during crises where access to the internet network, cloud services, or data centers is even more limited.

In this course, we will cover the basics of genome analysis to understand the speed-accuracy tradeoff in using computationally-lightweight heuristics versus accurate computationally-expensive algorithms. Such heuristic algorithms typically operate on a smaller dataset that can fit in the memory of today’s mobile device. Students will experimentally evaluate different heuristic algorithms and observe their effect on the end results. This evaluation will give the students the chance to carry out a hands-on project to implement one or more of these heuristic algorithms in their smartphones and help the society by enabling on-site analysis of genomic data.

Prerequisites of the course:

  • No prior knowledge in bioinformatics or genome analysis is required.
  • A good knowledge in C programming language and programming is required.
  • Interest in making things efficient and solving problems

The course is conducted in English.

Course description page
Moodle
Piazza

Mentors

Name E-mail Office
Lead Supervisor Mohammed Alser mohammed.alser@inf.ethz.ch CAB F 72
Supervisor Jeremie Kim jeremie.kim@inf.ethz.ch CAB E 78
Supervisor Can Firtina can.firtina@inf.ethz.ch CAB F 74.2
Supervisor Juan Gómez Luna juan.gomez@inf.ethz.ch CAB D 77
Supervisor Damla Senol Cali dsenol@andrew.cmu.edu

2020 Meetings/Schedule

Week Date Meeting Learning Materials Assignments
W1 29.09
Tue.
M1: P&S Mobile Genomics Course Presentation
(PDF) (PPT)
Video
Required Materials
Recommended Materials

Learning Materials

Meeting 1: Required Materials

Meeting 1: Recommended Materials

More Learning Materials

genome_seq_mobile.txt · Last modified: 2021/02/05 09:39 (external edit)