Uusi opinto-opas (sisältäen myös opetusohjelmat) lukuvuodelle 2018-2019 sijaitsee osoitteessa https://opas.peppi.utu.fi . Tältä sivustolta löytyvät enää vanhat opinto-oppaat ja opetusohjelmat.

The new study guide (incl. teaching schedules) for academic year 2018-2019 can be found at https://studyguide.utu.fi. This site contains only previous years' guides.

x !
Arkistoitu opetussuunnitelma 2013–2014
Selaamasi opetussuunnitelma ei ole enää voimassa. Tarkista tiedot voimassa olevasta opetussuunnitelmasta.
BIOI4450 High Throughput Data Analysis 5 op
Organised by
Person in charge
Matti Nykter
Planned organizing times
Period(s) I II III IV
2013–2014 X
Preceding studies

Learning outcomes

After the course, the student can:
- compare sequencing and microarray technologies used in high-throughput analysis and choose suitable ones for the analysis required.
- explain the principles of measurement technologies covered and how various inherent errors and biases of the measurement techniques affect the analysis.
- apply common methods and algorithms to extract information from microarray and sequencing measurements.
- discuss the statistical principles underlying the data analysis methods above and identify the benefits and weaknesses of each method.
- select suitable algorithms for the analysis and justify the choice.
- build data analysis pipelines for microarray and sequencing data analysis.


1. High throughput methods introduction, Flow cytometry
2. HT Genome sequencing: SNPs, CNVs
3. Gene expression: qRT-PCR
4. Gene expression: microarrays
5. Gene expression: RNA-Seq
6. Transcription factor binding: ChIP, ChIP-on-chip, ChIP-Seq

Teaching methods

Teaching method Contact Online
Lectures 20 h 12 h

Independent work by following the provided instructions. Work and learning must be documented by Moodle postings.

Teaching language


Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Doctoral Students
  • Exchange Students
Participation in classroom work
  • In English
  • In English
Written exam
  • In English
Participation in classroom work and Exercise(s) and Written exam


Numeric 0-5.

Recommended year of study

1. year spring

Study materials

Lecture notes and other material provided by the teacher

Further information

Organization Responsible: Tampere IBT

Belongs to following study modules

Tulevaisuuden teknologioiden laitos
Tulevaisuuden teknologioiden laitos
Tulevaisuuden teknologioiden laitos
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Implementation details are unavailable.
Tulevaisuuden teknologioiden laitos