Welcome to the MVE510 - Introduction to bioinformatics. This is course home page contains all the information you need to participate and complete the course.

The course will this year will be held at Chalmers campus with physical lectures and computer exercises.

 

Teachers

Erik Kristiansson, examiner, course administrator, lecturer

Juan Salvador Inda Diaz, computer exercise assistant

David Lund, computer exercise assistant

 

Student representatives (preliminary)

Antonia Freya Susanne Düx
Nils Ingelhag
Lisa-Marie Witte
Jewahri Idris Yousuf
Mercedes Dalman

Course aims, plan and schedule

Syllabus with course aims

Course plan

 

Course material

Please refer to the course plan for lecture-by-lecture reading instructions.

Lecture notes

• Lecture 1 (updated 2021-11-02)
• Lecture 2 (updated 2021-11-04), last year's lecture
• Lecture 3 (updated 2021-11-09), last year's lecture
• Lecture 4 (updated 2021-11-12), last year's lecture
• Lecture 5 (updated 2021-11-16), last year's lecture
• Lecture 6 (updated 2021-11-23),  last year's lecture 1, last year's lecture 2
• Lecture 7 (updated 2021-11-26), last year's lecture, last year's lecture 2
• Lecture 8, Notes on linear models, last year's lecture
• Lecture 9 (updated 2021-12-03), last year's lecture
• Lecture 10 (updated 2021-12-07), last year's lecture 
• Lecture 11, last year's lecture
• Lecture 12 (updated 2021-12-10)
• Lecture 13, 1928 Diagnostics, AstraZeneca
• Lecture 14, last year's slides, last year's lecture

Papers

The following scientific papers are a part of the literature of this course. 

• Lecture 2: Ten years of next-generation sequencing technology, van Dijk EL, Auger H, Jaszczyszyn Y, and Thermes C. Trends in Genetics, 30(10) 2014.
• Lecture 4: A beginner's guide to SNP calling from high-throughput DNA-sequencing data, Altmann A, Weber P, Bader D, Preuss M, Binder EB, and Müller-Myhsok B. Human Genetics, 131(10) 2012.
  Lecture 5 and 6: Mapping reads on a genomic sequence: an algorithmic overview and a practical comparative analysis. Schbath S, Martin V, Zytnicki M, Fayolle J, Loux V, and Gibrat JF. Journal of Computational Biology, 19(6) 2012.
• Lecture 7 and 8: Measuring differential gene expression with RNA-seq: challenges and strategies for data analysis, Finotello F and Di Camillo F. Briefings in Functional Genomics, 14(2) 2014.
• Lecture 9: Clustering. Naomi Altman and Martin Krzywinski. Nature Methods, 14(6) 2017.
• Lecture 9: Principal component analysis. Jake Lever, Martin Krzywinski, and Naomi Altman. Nature Methods, 14(7) 2017.
• Lecture 11: Integrative analysis of omics data, Österlund T, Cvijovic M, and Kristiansson E. Systems Biology, 6(1) 2017.
• Lecture 11-12: The road to metagenomics: from microbiology to DNA sequencing technologies and bioinformatics, Escobar-Zepeda A, de León AVP, and Sanchez-Flores A. Frontiers in Genetics, 6 2015.

Extra exercises

• Lecture 5

Optional course book

Xinkun Wang, Next-Generation Sequencing Data Analysis, CRC Press, ISBN 9781482217889. The course covers chapters 2-5, 7-9, and 13. 

 

Computer exercises

The course contains four compulsory computer exercises. Computer exercise 1 is examined at the scheduled exercise. Computer exercise 2, 3 and 4 should be handed in as written reports. The computer exercises should be made in groups of maximum two persons.

• Computer exercise 1
• Computer exercise 2, deadline 5th of December.
• Computer exercise 3, deadline 19th of December.
• Computer exercise 4, deadline 9th of January.

 

Software you need to install if you work from your own computer

• RStudio (https://rstudio.com/) or R (https://www.r-project.org/)
• IGV (http://software.broadinstitute.org/software/igv/)

Note that you can connect to the computers at Chalmers from remote. Please refer to https://it.portal.chalmers.se/itportal/Faq/RemoteAccess?setlang=en for full details. All software should be avilable for the computers in SalA as well as the computer rooms in the Chemistry and Math building.

 

Guidelines for writing and submitting reports

The reports submitted as a group (of maximum two persons) through the Canvas course page. The report should be either in PDF or WORD-format. All of the code necessary should be included in the end of the report as an Appendix. Please double check that the sumibbted code works as intended. Don't forget to add the names and Swedish social security number for all persons in the group at the front page. You only need to submit one report per group.

The reports should contain answers to all the questions posed in the exercise sheet. The answers should almost always have some motivation, meaning that even though the question could be answered with a yes or a no, we require a motivation why. Example question: "Do you see any differences?" Describe the observed differences (if the answer is yes), and not only a yes or a no. When you have been asked to generate a figure, this figure should be included in the report. The reports do not need an introduction, method, results, or discussion section, but should include some information about what has been done. Example: “When doing the quality assessment using fastqc, we saw that…”.

Good luck!

Exam

• 13 January 2022

Previous exams

• April 6, 2018
• August 29, 2018
• January 17, 2019, solutions
• April 26, 2019
• August 28, 2019, solutions
• January 16, 2020, solutions
• April 8, 2020
• January 13, 2021 (note that the year on the exam is wrong!)

Examination
This  course is examined based on,

• Written exam: 08:30 on January 13, 2022. This gives you 5 hp and determines your grade in the course.
• Four compulsory computer exercises. When you have passed all four of them you earn 2.5 hp.