T-61.5050 High-throughput bioinformatics V P, 5/7 cr

(Title in Finnish: T-61.5050 Suurkapasiteettimittausten bioinformatiikka V L)

Lecturers	D.Sc.(Tech) Janne Nikkilä, Laboratory of Computer and Information Science, Doc. Petri Auvinen, Institute of Biotechnology, D.Sc. Alvis Brazma, European Bioinformatics Institute, Microarray group
Assistant	M.Sc. Merja Oja, Laboratory of Computer and Information Science
Credits	5 or 7
Semester	Spring 2007 (during periods III and IV)
Lectures	On Thursdays at 14-16 in room T3 in the computer science building, Konemiehentie 2, Otaniemi, Espoo. The first lecture on 18.1.2007.
Exercises	On Thursdays at 16-18 in room A328.
Language	English
Web	http://www.cis.hut.fi/Opinnot/T-61.5050/
E-mail	t615050@cis.hut.fi

• Introduction
• Prerequisites for attending
• Course format
• Signing up for the course
• Literature
• Homework assignment
• Course schedule
• One page summary/brochure

Introduction [back to top]

This year the topic is data analysis for gene expression.

Microarray technology has made it possible to monitor large-scale gene expression (the level of activation of genes) and has become incredibly popular in genomics research. This high-throughput technique can provide information for thousands of genes in parallel and is producing huge amount of valuable data. Data sets can easily have tens, hundreds of thousands or even millions of data points. This necessitates use of sophisticated data-analysis tools for processing and data mining of this type of genomic data, to understand the underlying genetic networks and to answer the complex biological and medical questions involved

This course is designed to introduce computational and statistical concepts and tools necessary to analyse microarray-based gene expression data, a skill that is in high demand by biotechnology, bioinformatics and pharmaceutical companies. The skills learned in this course will also be applicable to other problems involving large data sets, such as proteomics, and more generally in data mining.

Prerequisites for attending [back to top]

This course is intended mainly for advanced undergraduate (Master's level) and doctoral students and of computer science, statistics, and applied mathematics, but students from other fields are welcome as well. In particular mathematically oriented biology, bioinformatics, and medical students should benefit from the course.

Basic knowledge of probability, statistics, vector algebra, and calculus is assumed (the basic mathematics courses in HUT). A "Basic course in bioinformatics", such as S-114.2510 Computational Systems Biology or equivalent background is assumed as well.

Course format [back to top]

The course contains the following parts: lectures, exercise sessions, homework assignments, an intensive course (Tue 10-12, Thu 14-16 and Fri 14-16, between 13.2.-1.3.) and an exam.

Signing up for the course [back to top]

HUT students:	In Webtopi
Other universities:	Send email to the organizers or sign up at the introduction lecture.

Course material [back to top]

The lectures will be based on the book: Sorin Draghici, Data analysis tools for DNA microarrays (2003)

The lecture slides are available only for course participants. The lecture_notes/ directory is password protected. Course participants have received an e-mail about this. If you do not yet have the password please send e-mail to the course assistant.

List of material covered in the course can be found from here.

Some links to tutorials on how to use R can be found from:

• R-tutorial
• R reference card listing useful commands
• Manuals at www.r-project.org

Homework assignment [back to top]

The description of the homework assignment is here. The dead line for returning the exercise is the 27th of May. The dead line is strict. The report and the code used in the assignment should be returned by e-mail (t615050@cis.hut.fi).

The data set for the assignment can be retrived from here. Note that the data directory is password protected. The password is the same as the one that can be used to acces the lecture notes. It has been e-mailed to course participants.

Course feedback [back to top]

A course feedback form for this course can be found through links from the page http://www.cs.hut.fi/Opinnot/Palaute/kurssipalaute-en.html. You should fill in the form by May 23rd.

Course schedule [back to top]

Time	Lecturer	Subject
Thu 18.1.	Petri, Janne, Merja	Introduction + administrative issues [Slides 4/page (password protected)] Basics of biology (Draghici: Ch 1 + a lot of extra material)
Thu 25.1.	Petri, Janne	Lecture: Microarrays (Draghici: Ch 2 and 3 + a lot of extra material)
Thu 1.2.	Janne, Merja	Lecture: Preprocessing and normalization of microarrays (Draghici: Ch. 3, 4, 8 and 12 + some extra material) [Slides 4/page (password protected)] Exercise: Basics of Biology + Microarrays [Exercise questions] [Model answers]
Thu 9.2.	Janne, Merja	Lecture: Basic hypothesis testing for microarray data (Draghici: 5, 6, 7, 9, and 13 + some extra material) [Slides 4/page (password protected)] Exercise: Preprocessing and normalization of microarrays [Exercise questions] [Exercise answers] [R commands for reading microarray data] [R commands for normalization]
Tue 13.2.- Thu 1.3.	Alvis Brazma	Intensive course (Tue 10-12, Thu 14-16 and Fri 14-16): Practical course in microarray data analysis Location: University of Helsinki, Kumpula campus, Exactum, room B119.
15.3.	Janne, Merja	Lecture: Visualization of HT data (Dragichi Ch 10 + some extra material) [Slides 4/page (password protected)] Exercise: Basic hypothesis testing for microarray data [Exercise questions] [Data set] [Exercise answers]
22.3.	Janne, Merja	Clustering of high-throughput data [Slides 4/page (password protected)] Exercise: Visualization methods [Exercise questions] [Data set] [Exercise answers]
25.3.		Deadline for returning the report on the homework assignment given at the intensive course part: Practical course in microarray data analysis
29.3.	Janne, Merja	Lecture cancelled Exercise: Clustering [Exercise questions] [Data set] [Exercise answers]
12.4.	Janne, Merja	Lecture: Classification of HT data. [Slides 4/page (password protected)] No exercise, because last lecture was postoned.
19.4.	Janne, Merja	Lecture: Mass Spectrometry data. [Slides 4/page (password protected)] Exercise: Classification [Exercise questions] [Data set] [Exercise answers]
26.4.	Janne, Merja	Summary lecture (recap of course contents) Exercise: Demo of Mzmine, a tool for processing mass spectometry data
3.5.	Janne, Merja	Lecture replaced by a special recap exercise session. Come and ask about the exercises! 14-16 Exercise, 16-18 nothing
8.5.		The exam at 9-12 in T1. Sign in using WWWTopi. What you should read.
25.5.		Last opportunity to give course feedback
27.5.		Deadline for the homework assignment

For more information, please send email to t615050@cis.hut.fi.