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Tampere University Student’s Guide

Course unit, curriculum year 2026–2027
BBT.BI.203

High-throughput Sequencing Data Analysis, 5 cr

Tampere University
Teaching periods
Active in period 3 (1.1.2027–7.3.2027)
Active in period 4 (8.3.2027–31.5.2027)
Course code
BBT.BI.203
Language of learning
English
Academic years
2024–2025, 2025–2026, 2026–2027
Level of study
Advanced studies
Grading scale
General scale, 0-5
Persons responsible
Responsible teacher:
Juha Kesseli
Responsible organisation
Faculty of Medicine and Health Technology 100 %
Coordinating organisation
MET Studies 100 %
Content

Contents:

  • Characteristics of sequencing data
  • Quality control

  • Bulk and single-cell data

  • High-throughput count data modeling

  • MDS, tSNE, UMAP

  • Data analysis pipeline design

  • Common state-of-the-art algorithms and statistics for data analysis, for a variety of data types

  • Basic approaches for data integration

Learning outcomes
Compulsory prerequisites
Learning material
Equivalences
Studies that include this course
Completion option 1
Lectures, exercises and project work.

Participation in teaching

Contact teaching
07.01.2027 – 06.05.2027
Active in period 3 (1.1.2027–7.3.2027)
Active in period 4 (8.3.2027–31.5.2027)