Opinto-opas 2020-2022

After passing this course, the students will know how the R statistical environment can be used for biological data analysis. The students will be able to use R for analyzing diverse data types from very different biological experiments, including high-throughput sequencing data. In addition to analyzing such data, they can help experimental scientists in the interpretation. The student can retrieve R extension libraries on-line and take them into use, and can describe main uses of the components in the BioConductor package.

The course consists of lectures, which introduce the theoretical aspects of selected methodologies, and of in-class and homework exercises, which teach the practical aspects of performing analyses of biological data. The following topics will be covered:

1. Introduction to R statistical environment
2. Practicing R programming
3. Simple sequence analysis
4. Annotating gene groups
5. Next-generation sequencing: introduction and genomic applications
6. Transcriptomics: gene expression microarrays and qRT-PCR
7. Next-generation sequencing in transcriptomics: RNA-seq experiments
8. Deciphering the regulome: from ChIP to ChIP-seq

Exercises, participation in classroom work, written exam

Lectures, exercises

Lecture notes, other material provided by the teacher

NOTE: The minor subject module in bioinformatics will be available only until 31 July 2022.

1. Ortutay and Ortutay: Molecular Data Analysis Using R. John Wiley & Sons, Inc. 2016. 978-1-119-16502-6

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englanti

Syventävät opinnot

Bioinformatics

Csaba Ortutay