Course syllabus

On this page and in the course PM, you will find all the information about the course! All relevant files are collected under Files and linked below, and the reports for the computer exercises are submitted under Assignments. Questions are primarily answered during classes, but you can also post questions on the course website under Discussions. Specific coding questions about the computer exercises are answered by the teaching assistants during the scheduled computer labs. The information on the page will be updated continuously during the course, so please activate notifications for Announcements.

If you find any errors on the course website, please notify Anna.

Syllabus, Schedule & Course PM

• Syllabus with course aims
• Schedule
• Course PM 

Teachers

Lecturer & course administrator: Anna Johnning
Examiner: Erik Kristiansson
Teaching assistants: Sophia Axillus, James Butler & Laleh Varghaei

Course material

The course is based on the following material that is available to download from the Canvas course page,

• Lecture notes
• Eight academic papers
• Exercises on sequence alignment

There is also an optional course book, where the course covers chapters 2–5, 7–9, and 13. A few copies are available from the Chalmers library.

• Next-Generation Sequencing Data Analysis by Xinkun Wang. 
  • Hardback: ISBN 9780367349899
  • Ebook: ISBN 9780429329180

* These timings are approximate, as some material might spill over to the next scheduled lecture. 

Examination

This course is examined based on,

• Written exam (5 hp, grade U–5)
• Four compulsory computer exercises (2.5 hp, U/G) 

The course has no elements that generate bonus points for the written exam.

Written Exam

A passed exam is worth 5 credits and determines your grade in the course. The maximum score is 40 points; a pass requires at least 18 points, a grade of 4 requires 26 points, and a grade of 5 requires 34 points. No aids are allowed during the exam. Shortly after the exam, suggested solutions will be posted on Canvas. Old exams, along with some answers/solutions, can be found here.

This year's exams will be given on,

• Thursday morning, January 14th
• Wednesday morning, March 31th
• Friday morning, August 27th. 

Computer exercises

The course contains four compulsory computer exercises. The purpose of the computer exercises is to,

• Gain hands-on experience in bioinformatic analyses
• Apply concepts covered by the lectures in realistic situations
• Interpret and critically evaluate the results
• Practice programming

Computer Exercise 1 is examined during the scheduled computer labs by the teaching assistants. Computer Exercise 2–4 are examined through written reports. Each exercise should be done in groups of a maximum of two students. 

It is highly recommended to submit the reports at your earliest convenienvce, but no lated than the deadlines listed under Assignments. Make sure you plan your work so that you can utilise the help from the teaching assistants during the scheduled computer labs.

Here is a suggested time plan where "X" marks the deadlines and the scheduled computer labs are marked at the bottom (high bar = 4 h lab, low bar =  2 h lab),

If you want to complete the exercises on your own computer, you can either access the relevant software through https://apps.chalmers.se/ or install the following:

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

All software are available on the computers in computer rooms HB105, HB110, KD1, KD2, M10, and MT11.

More information about the computer exercises – including instructions, deadlines, and the format of the reports – is found under Assignment.

Use of AI tools

Course evaluation

Please feel free to discuss with us, the teachers, how the course can be improved at any time during the course! You can also provide feedback through the student representatives listed below, particilarly before the mid-course meeting on Thursday, November 26, at 12:00 (study week 4), and before the course board meeting (date TBD). At the end of the course, we would greatly appreciate your completing the course survey. Your feedback helps us identigy what works well and what should be improved for futer course iterations.

Ebba Ebenfelt (MPBIO)
Celina Hörnquist (MPBIO)
Rebecka Öhman (MPBIO)
Albin Jonsson (MPENM)
Philip Ohlsson (MPIDE)