Specialised Bio-informatics and Data Analysis for Genetic Analysis
   
Reference DHBIOM00000030
Taught in Majors List Master of Biomedical Sciences
Theory (A) 15.0
Exercises (B) 25.0
Training and projects (C) 0.0
Studytime (D) 120.0
Studypoints (E) 4
Level  
Credit contract? Access is determined after successful competences assessment
Examination contract? This course can not be taken through this kind of contract
Credit contract mandatory if Exam contract? Separate credit contract mandatory
Retake possible in case of permanent evaluation? Yes
Teaching Language Dutch
Lecturer Jo Vandesompele
Department GE02
Co-lecturers Jan Hellemans
Filip Pattyn
Katleen De Preter
Key Words

gene expression, data analysis, scripting language task automation, biostatistics

Position of the Course

Current biomedical research generates a multitude of data that requires specific analysis methods. This course make students familiar with advanced bio-informatics and biostatistical methods to analyse microarray and real-time PCR gene expression data. Students must be able to interpret and understand analyses in scientific publications, and to perform independent analyses on publically available datasets. Students are also made familiar with association studies and scripting languages for task automation.

Contents

  • Focus on high troughput (microarray) data analysis and the use of scripting languages for task automation and data analysis.
  • Explorative ans supervized data analysis (hierarchical clustering, PCA, self organizing maps, SAM, PAM, support vector machines, ..
  • Analysis of signaling pathways (onto-express, genmapp, ...)
  • Analysis of real time PCR data and error propagation
  • Biostatistical evaluation of gene expression (parametric, non parametric, confidence intervals
  • Literature/text data mining
  • Introduction to data analysis for linking and association studies

Starting Competences

Having successfully completed the courses Data analysis II: biomedical statistics, Informatics I and Informatics II from the bachelor program biomedical sciences, or having acquired the relevant ending objectives by other means.

Final Competences

  • Having a thorough knowledge of advanced bio-informatics and biostatistical methods for analysing microarray and real time PCR gene expression data
  • Being familiar with linking and association studies and with scripting languages for task automation.

Teaching and Learning Material

15 EUR, dutch and english, software that will be made available, PowerPoint presentations, copies from books

References

  • Intuitive biostatistics, Oxford University Press, New York, 1995, ISBN: 0-19-50-8607-4
  • The R book, John Wiley & Sons, West sussex, 2007, ISBN: 978-0-470-51024-7

Course Content-Related Study Coaching

interactive support through Minverva, personal contact after electronic appointment

Teaching Methods

Classroom lectures; ; Microteaching

Evaluation Moments

Evaluation throughout semester as well as during examination period

Evaluation Methods

During examination period: written open-book exam - problems; written closed-book exam
During semester: Assessment of participation in and reporting of the group work. Second chance: Not possible
Frequency: once

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